Search Results for author: Jiawei Zhang

Found 187 papers, 58 papers with code

Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis

1 code implementation ICCV 2023 Jiahe Li, Jiawei Zhang, Xiao Bai, Jun Zhou, Lin Gu

This paper presents ER-NeRF, a novel conditional Neural Radiance Fields (NeRF) based architecture for talking portrait synthesis that can concurrently achieve fast convergence, real-time rendering, and state-of-the-art performance with small model size.

SEGEN: Sample-Ensemble Genetic Evolutional Network Model

1 code implementation23 Mar 2018 Jiawei Zhang, Limeng Cui, Fisher B. Gouza

Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.

Ensemble Learning Representation Learning

Cross-Scale Internal Graph Neural Network for Image Super-Resolution

1 code implementation NeurIPS 2020 Shangchen Zhou, Jiawei Zhang, WangMeng Zuo, Chen Change Loy

Specifically, we dynamically construct a cross-scale graph by searching k-nearest neighboring patches in the downsampled LR image for each query patch in the LR image.

Image Restoration Image Super-Resolution

Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Dataset Augmented by ChatGPT

1 code implementation Preprint 2023 Jiawei Zhang

Inspired by the latest ChatGPT and Toolformer models, we propose the Graph-ToolFormer (Graph Reasoning oriented Toolformer) framework to teach LLMs themselves with prompts augmented by ChatGPT to use external graph reasoning API tools.

Community Detection Graph Classification +7

Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT

1 code implementation10 Apr 2023 Jiawei Zhang

To address such challenges, in this paper, we will investigate the principles, methodologies and algorithms to empower existing LLMs with graph reasoning ability, which will have tremendous impacts on the current research of both LLMs and graph learning.

Graph Learning Knowledge Graphs +3

Spatio-Temporal Filter Adaptive Network for Video Deblurring

1 code implementation ICCV 2019 Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, WangMeng Zuo, Jimmy Ren

To overcome the limitation of separate optical flow estimation, we propose a Spatio-Temporal Filter Adaptive Network (STFAN) for the alignment and deblurring in a unified framework.

Ranked #3 on Deblurring on DVD (using extra training data)

Deblurring Image Deblurring +1

DAVANet: Stereo Deblurring with View Aggregation

1 code implementation CVPR 2019 Shangchen Zhou, Jiawei Zhang, WangMeng Zuo, Haozhe Xie, Jinshan Pan, Jimmy Ren

Nowadays stereo cameras are more commonly adopted in emerging devices such as dual-lens smartphones and unmanned aerial vehicles.

Deblurring Image Deblurring

Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

2 code implementations7 Nov 2022 Andrey Ignatov, Radu Timofte, Maurizio Denna, Abdel Younes, Ganzorig Gankhuyag, Jingang Huh, Myeong Kyun Kim, Kihwan Yoon, Hyeon-Cheol Moon, Seungho Lee, Yoonsik Choe, Jinwoo Jeong, Sungjei Kim, Maciej Smyl, Tomasz Latkowski, Pawel Kubik, Michal Sokolski, Yujie Ma, Jiahao Chao, Zhou Zhou, Hongfan Gao, Zhengfeng Yang, Zhenbing Zeng, Zhengyang Zhuge, Chenghua Li, Dan Zhu, Mengdi Sun, Ran Duan, Yan Gao, Lingshun Kong, Long Sun, Xiang Li, Xingdong Zhang, Jiawei Zhang, Yaqi Wu, Jinshan Pan, Gaocheng Yu, Jin Zhang, Feng Zhang, Zhe Ma, Hongbin Wang, Hojin Cho, Steve Kim, Huaen Li, Yanbo Ma, Ziwei Luo, Youwei Li, Lei Yu, Zhihong Wen, Qi Wu, Haoqiang Fan, Shuaicheng Liu, Lize Zhang, Zhikai Zong, Jeremy Kwon, Junxi Zhang, Mengyuan Li, Nianxiang Fu, Guanchen Ding, Han Zhu, Zhenzhong Chen, Gen Li, Yuanfan Zhang, Lei Sun, Dafeng Zhang, Neo Yang, Fitz Liu, Jerry Zhao, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Shota Hirose, Kasidis Arunruangsirilert, Luo Ao, Ho Chun Leung, Andrew Wei, Jie Liu, Qiang Liu, Dahai Yu, Ao Li, Lei Luo, Ce Zhu, Seongmin Hong, Dongwon Park, Joonhee Lee, Byeong Hyun Lee, Seunggyu Lee, Se Young Chun, Ruiyuan He, Xuhao Jiang, Haihang Ruan, Xinjian Zhang, Jing Liu, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He

While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.

Image Super-Resolution

RestoreFormer++: Towards Real-World Blind Face Restoration from Undegraded Key-Value Pairs

1 code implementation14 Aug 2023 Zhouxia Wang, Jiawei Zhang, Tianshui Chen, Wenping Wang, Ping Luo

In this work, we propose RestoreFormer++, which on the one hand introduces fully-spatial attention mechanisms to model the contextual information and the interplay with the priors, and on the other hand, explores an extending degrading model to help generate more realistic degraded face images to alleviate the synthetic-to-real-world gap.

Blind Face Restoration

DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization

1 code implementation11 Mar 2024 Jiahe Li, Jiawei Zhang, Xiao Bai, Jin Zheng, Xin Ning, Jun Zhou, Lin Gu

Our motivation stems from the highly efficient representation and surprising quality of the recent 3D Gaussian Splatting, despite it will encounter a geometry degradation when input views decrease.

Novel View Synthesis

Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision

1 code implementation ICCV 2021 Zhilu Zhang, Haolin Wang, Ming Liu, Ruohao Wang, Jiawei Zhang, WangMeng Zuo

To diminish the effect of color inconsistency in image alignment, we introduce to use a global color mapping (GCM) module to generate an initial sRGB image given the input raw image, which can keep the spatial location of the pixels unchanged, and the target sRGB image is utilized to guide GCM for converting the color towards it.

Optical Flow Estimation

Heterogeneous Deep Graph Infomax

1 code implementation19 Nov 2019 Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai, Liefeng Bo, Jiawei Zhang

The derived node representations can be used to serve various downstream tasks, such as node classification and node clustering.

Classification Clustering +4

Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

1 code implementation14 Aug 2021 Ziwei Fan, Zhiwei Liu, Jiawei Zhang, Yun Xiong, Lei Zheng, Philip S. Yu

Therefore, we propose to unify sequential patterns and temporal collaborative signals to improve the quality of recommendation, which is rather challenging.

Sequential Recommendation

Revisiting Domain Generalized Stereo Matching Networks from a Feature Consistency Perspective

1 code implementation CVPR 2022 Jiawei Zhang, Xiang Wang, Xiao Bai, Chen Wang, Lei Huang, Yimin Chen, Lin Gu, Jun Zhou, Tatsuya Harada, Edwin R. Hancock

The stereo contrastive feature loss function explicitly constrains the consistency between learned features of matching pixel pairs which are observations of the same 3D points.

Contrastive Learning Stereo Matching

TI-CNN: Convolutional Neural Networks for Fake News Detection

2 code implementations3 Jun 2018 Yang Yang, Lei Zheng, Jiawei Zhang, Qingcai Cui, Zhoujun Li, Philip S. Yu

By projecting the explicit and latent features into a unified feature space, TI-CNN is trained with both the text and image information simultaneously.

Fact Checking Fake News Detection

Deep Blind Video Super-resolution

2 code implementations ICCV 2021 Jinshan Pan, Songsheng Cheng, Jiawei Zhang, Jinhui Tang

Existing video super-resolution (SR) algorithms usually assume that the blur kernels in the degradation process are known and do not model the blur kernels in the restoration.

Image Deconvolution Image Restoration +2

Spectral Collaborative Filtering

1 code implementation30 Aug 2018 Lei Zheng, Chun-Ta Lu, Fei Jiang, Jiawei Zhang, Philip S. Yu

Benefiting from the rich information of connectivity existing in the \textit{spectral domain}, SpectralCF is capable of discovering deep connections between users and items and therefore, alleviates the \textit{cold-start} problem for CF.

Collaborative Filtering Recommendation Systems

Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks

1 code implementation CVPR 2018 Jiawei Zhang, Jinshan Pan, Jimmy Ren, Yibing Song, Linchao Bao, Rynson W. H. Lau, Ming-Hsuan Yang

The proposed network is composed of three deep convolutional neural networks (CNNs) and a recurrent neural network (RNN).

Ranked #9 on Deblurring on RealBlur-R (trained on GoPro) (SSIM (sRGB) metric)

Deblurring

Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning

3 code implementations22 Sep 2020 Yizhu Jiao, Yun Xiong, Jiawei Zhang, Yao Zhang, Tianqi Zhang, Yangyong Zhu

Instead of learning on the complete input graph data, with a novel data augmentation strategy, \textsc{Subg-Con} learns node representations through a contrastive loss defined based on subgraphs sampled from the original graph instead.

Data Augmentation Graph Representation Learning +2

Social Network Fusion and Mining: A Survey

1 code implementation26 Apr 2018 Jiawei Zhang

Meanwhile, in such an age of online social media, users usually participate in multiple online social networks simultaneously to enjoy more social networks services, who can act as bridges connecting different networks together.

Social and Information Networks Computers and Society

Learning Selfie-Friendly Abstraction from Artistic Style Images

1 code implementation5 May 2018 Yicun Liu, Jimmy Ren, Jianbo Liu, Jiawei Zhang, Xiaohao Chen

Artistic style transfer can be thought as a process to generate different versions of abstraction of the original image.

Style Transfer

Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networks

1 code implementation3 Sep 2018 Yuan Yuan, Siyuan Liu, Jiawei Zhang, Yongbing Zhang, Chao Dong, Liang Lin

We consider the single image super-resolution problem in a more general case that the low-/high-resolution pairs and the down-sampling process are unavailable.

Image Super-Resolution Image-to-Image Translation +1

Benchmarking Large Multimodal Models against Common Corruptions

1 code implementation22 Jan 2024 Jiawei Zhang, Tianyu Pang, Chao Du, Yi Ren, Bo Li, Min Lin

This technical report aims to fill a deficiency in the assessment of large multimodal models (LMMs) by specifically examining the self-consistency of their outputs when subjected to common corruptions.

Benchmarking

Graph Neural Distance Metric Learning with Graph-Bert

1 code implementation9 Feb 2020 Jiawei Zhang

Extensive experiments have been done on several benchmark graph datasets, and the results demonstrate that GB-DISTANCE can out-perform the existing baseline methods, especially the recent graph neural network model based graph metrics, with a significant gap in computing the graph distance.

Clustering Graph Classification +4

Segmented Graph-Bert for Graph Instance Modeling

1 code implementation9 Feb 2020 Jiawei Zhang

In this paper, we will examine the effectiveness of GRAPH-BERT on graph instance representation learning, which was designed for node representation learning tasks originally.

Graph Classification Representation Learning

Robust Synthetic-to-Real Transfer for Stereo Matching

1 code implementation12 Mar 2024 Jiawei Zhang, Jiahe Li, Lei Huang, Xiaohan Yu, Lin Gu, Jin Zheng, Xiao Bai

With advancements in domain generalized stereo matching networks, models pre-trained on synthetic data demonstrate strong robustness to unseen domains.

Domain Generalization Pseudo Label +1

Continuous-Time Relationship Prediction in Dynamic Heterogeneous Information Networks

1 code implementation30 Sep 2017 Sina Sajadmanesh, Sogol Bazargani, Jiawei Zhang, Hamid R. Rabiee

In this paper, we try to solve the problem of continuous-time relationship prediction in dynamic and heterogeneous information networks.

Link Prediction

Graph Collaborative Signals Denoising and Augmentation for Recommendation

1 code implementation6 Apr 2023 Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S. Yu

Moreover, we show that the inclusion of user-user and item-item correlations can improve recommendations for users with both abundant and insufficient interactions.

Collaborative Filtering Denoising +1

Dual Intents Graph Modeling for User-centric Group Discovery

1 code implementation9 Aug 2023 Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang

Therefore, user-centric group discovery task, i. e., recommending groups to users can help both users' online experiences and platforms' long-term developments.

Representation Learning Self-Supervised Learning

GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation

2 code implementations12 Sep 2019 Jiawei Zhang, Lin Meng

Analysis about the causes of the suspended animation problem with existing GNNs will be provided in this paper, whereas several other peripheral factors that will impact the problem will be reported as well.

Node Classification

Learning a Reinforced Agent for Flexible Exposure Bracketing Selection

1 code implementation CVPR 2020 Zhouxia Wang, Jiawei Zhang, Mude Lin, Jiong Wang, Ping Luo, Jimmy Ren

Automatically selecting exposure bracketing (images exposed differently) is important to obtain a high dynamic range image by using multi-exposure fusion.

Self-recoverable Adversarial Examples: A New Effective Protection Mechanism in Social Networks

1 code implementation26 Apr 2022 Jiawei Zhang, Jinwei Wang, Hao Wang, Xiangyang Luo

The destruction to DNNs brought by the adversarial attack sparks the potential that adversarial examples serve as a new protection mechanism for privacy security in social networks.

Adversarial Attack Adversarial Defense +1

ConsRec: Learning Consensus Behind Interactions for Group Recommendation

1 code implementation7 Feb 2023 Xixi Wu, Yun Xiong, Yao Zhang, Yizhu Jiao, Jiawei Zhang, Yangyong Zhu, Philip S. Yu

Since group activities have become very common in daily life, there is an urgent demand for generating recommendations for a group of users, referred to as group recommendation task.

MULTI-VIEW LEARNING

DiffuSum: Generation Enhanced Extractive Summarization with Diffusion

1 code implementation2 May 2023 Haopeng Zhang, Xiao Liu, Jiawei Zhang

This paper proposes DiffuSum, a novel paradigm for extractive summarization, by directly generating the desired summary sentence representations with diffusion models and extracting sentences based on sentence representation matching.

Extractive Summarization Sentence

HEGEL: Hypergraph Transformer for Long Document Summarization

1 code implementation9 Oct 2022 Haopeng Zhang, Xiao Liu, Jiawei Zhang

Extractive summarization for long documents is challenging due to the extended structured input context.

Document Summarization Extractive Summarization +1

JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation

1 code implementation18 Oct 2019 Zhiwei Liu, Lei Zheng, Jiawei Zhang, Jiayu Han, Philip S. Yu

JSCN will simultaneously operate multi-layer spectral convolutions on different graphs, and jointly learn a domain-invariant user representation with a domain adaptive user mapping module.

Recommendation Systems

Learning Diverse Tone Styles for Image Retouching

1 code implementation12 Jul 2022 Haolin Wang, Jiawei Zhang, Ming Liu, Xiaohe Wu, WangMeng Zuo

In particular, the style encoder predicts the target style representation of an input image, which serves as the conditional information in the RetouchNet for retouching, while the TSFlow maps the style representation vector into a Gaussian distribution in the forward pass.

Image Retouching

IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification

2 code implementations22 Jul 2019 Lin Meng, Jiawei Zhang

However, unlike such fields, it is hard to apply traditional deep learning models on the graph data due to the 'node-orderless' property.

General Classification Graph Classification +2

Deoscillated Graph Collaborative Filtering

1 code implementation4 Nov 2020 Zhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang, Philip S. Yu

Stacking multiple cross-hop propagation layers and locality layers constitutes the DGCF model, which models high-order CF signals adaptively to the locality of nodes and layers.

Collaborative Filtering Recommendation Systems

Double Sampling Randomized Smoothing

2 code implementations16 Jun 2022 Linyi Li, Jiawei Zhang, Tao Xie, Bo Li

To overcome this hurdle, we propose a Double Sampling Randomized Smoothing (DSRS) framework, which exploits the sampled probability from an additional smoothing distribution to tighten the robustness certification of the previous smoothed classifier.

FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural Network

2 code implementations22 May 2018 Jiawei Zhang, Bowen Dong, Philip S. Yu

This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance.

Fake News Detection

Graph Neural Lasso for Dynamic Network Regression

1 code implementation25 Jul 2019 Yixin Chen, Lin Meng, Jiawei Zhang

Experimental results provided on two networked sequence datasets, i. e., Nasdaq-100 and METR-LA, show that GNL can address the network regression problem very well and is also very competitive among the existing approaches.

regression

Progressive-Scale Boundary Blackbox Attack via Projective Gradient Estimation

1 code implementation10 Jun 2021 Jiawei Zhang, Linyi Li, Huichen Li, Xiaolu Zhang, Shuang Yang, Bo Li

In this paper, we show that such efficiency highly depends on the scale at which the attack is applied, and attacking at the optimal scale significantly improves the efficiency.

Face Recognition

DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing

1 code implementation28 Aug 2023 Jiawei Zhang, Zhongzhu Chen, huan zhang, Chaowei Xiao, Bo Li

Diffusion models have been leveraged to perform adversarial purification and thus provide both empirical and certified robustness for a standard model.

Denoising

CARE: Certifiably Robust Learning with Reasoning via Variational Inference

1 code implementation12 Sep 2022 Jiawei Zhang, Linyi Li, Ce Zhang, Bo Li

In particular, we propose a certifiably robust learning with reasoning pipeline (CARE), which consists of a learning component and a reasoning component.

Variational Inference

Improving Certified Robustness via Statistical Learning with Logical Reasoning

1 code implementation28 Feb 2020 Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang, Linyi Li, Hengzhi Pei, Bojan Karlas, Ji Liu, Heng Guo, Ce Zhang, Bo Li

Intensive algorithmic efforts have been made to enable the rapid improvements of certificated robustness for complex ML models recently.

BIG-bench Machine Learning Logical Reasoning

Iso-CapsNet: Isomorphic Capsule Network for Brain Graph Representation Learning

1 code implementation27 Jun 2022 Jiawei Zhang

Brain graph representation learning serves as the fundamental technique for brain diseases diagnosis.

Graph Representation Learning

VPNets: Volume-preserving neural networks for learning source-free dynamics

1 code implementation29 Apr 2022 Aiqing Zhu, Beibei Zhu, Jiawei Zhang, Yifa Tang, Jian Liu

We propose volume-preserving networks (VPNets) for learning unknown source-free dynamical systems using trajectory data.

SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding

1 code implementation27 Aug 2023 Xi Chen, Yongxiang Liao, Yun Xiong, Yao Zhang, Siwei Zhang, Jiawei Zhang, Yiheng Sun

Simultaneously, resource consumption of a single-GPU can be diminished by up to 69%, thus enabling the multiple GPU-based training and acceleration encompassing millions of nodes and billions of edges.

Graph Embedding

r-Instance Learning for Missing People Tweets Identification

no code implementations28 May 2018 Yang Yang, Haoyan Liu, Xia Hu, Jiawei Zhang, Xiao-Ming Zhang, Zhoujun Li, Philip S. Yu

The number of missing people (i. e., people who get lost) greatly increases in recent years.

GEN Model: An Alternative Approach to Deep Neural Network Models

no code implementations19 May 2018 Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we introduce an alternative approach, namely GEN (Genetic Evolution Network) Model, to the deep learning models.

Representation Learning

Reconciled Polynomial Machine: A Unified Representation of Shallow and Deep Learning Models

no code implementations19 May 2018 Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we aim at introducing a new machine learning model, namely reconciled polynomial machine, which can provide a unified representation of existing shallow and deep machine learning models.

BIG-bench Machine Learning

Deep Loopy Neural Network Model for Graph Structured Data Representation Learning

no code implementations19 May 2018 Jiawei Zhang

Existing deep learning models may encounter great challenges in handling graph structured data.

Representation Learning

On Deep Ensemble Learning from a Function Approximation Perspective

no code implementations19 May 2018 Jiawei Zhang, Limeng Cui, Fisher B. Gouza

In this paper, we propose to provide a general ensemble learning framework based on deep learning models.

Ensemble Learning

GADAM: Genetic-Evolutionary ADAM for Deep Neural Network Optimization

no code implementations19 May 2018 Jiawei Zhang, Fisher B. Gouza

Deep neural network learning can be formulated as a non-convex optimization problem.

CREST: Convolutional Residual Learning for Visual Tracking

no code implementations ICCV 2017 Yibing Song, Chao Ma, Lijun Gong, Jiawei Zhang, Rynson Lau, Ming-Hsuan Yang

Our method integrates feature extraction, response map generation as well as model update into the neural networks for an end-to-end training.

Visual Tracking

Fast Preprocessing for Robust Face Sketch Synthesis

no code implementations1 Aug 2017 Yibing Song, Jiawei Zhang, Linchao Bao, Qingxiong Yang

Exemplar-based face sketch synthesis methods usually meet the challenging problem that input photos are captured in different lighting conditions from training photos.

Face Sketch Synthesis

NPGLM: A Non-Parametric Method for Temporal Link Prediction

no code implementations21 Jun 2017 Sina Sajadmanesh, Jiawei Zhang, Hamid R. Rabiee

In this paper, we try to solve the problem of temporal link prediction in information networks.

Link Prediction

Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution

no code implementations CVPR 2017 Jiawei Zhang, Jinshan Pan, Wei-Sheng Lai, Rynson Lau, Ming-Hsuan Yang

In this paper, we propose a fully convolutional networks for iterative non-blind deconvolution We decompose the non-blind deconvolution problem into image denoising and image deconvolution.

Image Deconvolution Image Denoising

3D Hand Pose Tracking and Estimation Using Stereo Matching

no code implementations23 Oct 2016 Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, Xiaobin Xu, Qingxiong Yang

This paper demonstrates that the performance of the state-of-the art tracking/estimation algorithms can be maintained with most stereo matching algorithms on the proposed benchmark, as long as the hand segmentation is correct.

Hand Segmentation Pose Tracking +2

RGBD Salient Object Detection via Deep Fusion

no code implementations12 Jul 2016 Liangqiong Qu, Shengfeng He, Jiawei Zhang, Jiandong Tian, Yandong Tang, Qingxiong Yang

Numerous efforts have been made to design different low level saliency cues for the RGBD saliency detection, such as color or depth contrast features, background and color compactness priors.

Object object-detection +4

Multi-Source Multi-View Clustering via Discrepancy Penalty

no code implementations14 Apr 2016 Weixiang Shao, Jiawei Zhang, Lifang He, Philip S. Yu

In many real-world applications, information can be gathered from multiple sources, while each source can contain multiple views, which are more cohesive for learning.

Clustering

Bicycle-Sharing System Analysis and Trip Prediction

no code implementations3 Apr 2016 Jiawei Zhang, Xiao Pan, Moyin Li, Philip S. Yu

In bicycle-sharing systems, people can borrow and return bikes at any stations in the service region very conveniently.

Predicting Social Links for New Users across Aligned Heterogeneous Social Networks

no code implementations13 Oct 2013 Jiawei Zhang, Xiangnan Kong, Philip S. Yu

We propose a link prediction method called SCAN-PS (Supervised Cross Aligned Networks link prediction with Personalized Sampling), to solve the link prediction problem for new users with information transferred from both the existing active users in the target network and other source networks through aligned accounts.

Link Prediction Transfer Learning

BL-MNE: Emerging Heterogeneous Social Network Embedding through Broad Learning with Aligned Autoencoder

no code implementations26 Nov 2017 Jiawei Zhang, Congying Xia, Chenwei Zhang, Limeng Cui, Yanjie Fu, Philip S. Yu

The closeness among users in the networks are defined as the meta proximity scores, which will be fed into DIME to learn the embedding vectors of users in the emerging network.

Social and Information Networks Databases

Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models

no code implementations1 Aug 2018 Jiawei Zhang, Yang Wang, Piero Molino, Lezhi Li, David S. Ebert

We present Manifold, a framework that utilizes visual analysis techniques to support interpretation, debugging, and comparison of machine learning models in a more transparent and interactive manner.

BIG-bench Machine Learning

Physics-Based Generative Adversarial Models for Image Restoration and Beyond

no code implementations2 Aug 2018 Jinshan Pan, Jiangxin Dong, Yang Liu, Jiawei Zhang, Jimmy Ren, Jinhui Tang, Yu-Wing Tai, Ming-Hsuan Yang

We present an algorithm to directly solve numerous image restoration problems (e. g., image deblurring, image dehazing, image deraining, etc.).

Deblurring Image Deblurring +3

A Self-Organizing Tensor Architecture for Multi-View Clustering

no code implementations18 Oct 2018 Lifang He, Chun-Ta Lu, Yong Chen, Jiawei Zhang, Linlin Shen, Philip S. Yu, Fei Wang

In many real-world applications, data are often unlabeled and comprised of different representations/views which often provide information complementary to each other.

Clustering

Data-driven Blockbuster Planning on Online Movie Knowledge Library

no code implementations24 Oct 2018 Ye Liu, Jiawei Zhang, Chenwei Zhang, Philip S. Yu

After a thorough investigation of an online movie knowledge library, a novel movie planning framework "Blockbuster Planning with Maximized Movie Configuration Acquaintance" (BigMovie) is introduced in this paper.

Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement

no code implementations22 Nov 2018 Yibing Song, Jiawei Zhang, Lijun Gong, Shengfeng He, Linchao Bao, Jinshan Pan, Qingxiong Yang, Ming-Hsuan Yang

We first propose a facial component guided deep Convolutional Neural Network (CNN) to restore a coarse face image, which is denoted as the base image where the facial component is automatically generated from the input face image.

Deblurring Face Hallucination +2

MDU-Net: Multi-scale Densely Connected U-Net for biomedical image segmentation

no code implementations2 Dec 2018 Jiawei Zhang, Yuzhen Jin, Jilan Xu, Xiaowei Xu, Yanchun Zhang

The three multi-scale dense connections improve U-net performance by up to 1. 8% on test A and 3. 5% on test B in the MICCAI Gland dataset.

Image Segmentation Quantization +2

Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation

no code implementations NeurIPS 2018 Wenqi Ren, Jiawei Zhang, Lin Ma, Jinshan Pan, Xiaochun Cao, WangMeng Zuo, Wei Liu, Ming-Hsuan Yang

In this paper, we present a deep convolutional neural network to capture the inherent properties of image degradation, which can handle different kernels and saturated pixels in a unified framework.

Deblurring

Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification

no code implementations ECCV 2018 Xing Wei, Yue Zhang, Yihong Gong, Jiawei Zhang, Nanning Zheng

The reason is that the bilinear feature matrix is sensitive to the magnitudes and correlations of local CNN feature elements which can be measured by its singular values.

Fine-Grained Image Classification Fine-Grained Visual Recognition +1

Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae

no code implementations ICLR 2019 Piero Molino, Yang Wang, Jiawei Zhang

Embeddings are a fundamental component of many modern machine learning and natural language processing models.

SEGEN: SAMPLE-ENSEMBLE GENETIC EVOLUTIONARY NETWORK MODEL

no code implementations ICLR 2019 Jiawei Zhang, Limeng Cui, Fisher B. Gouza

Deep learning, a rebranding of deep neural network research works, has achieved a remarkable success in recent years.

Ensemble Learning Representation Learning

Gradient Descent based Optimization Algorithms for Deep Learning Models Training

no code implementations11 Mar 2019 Jiawei Zhang

In back propagation, the model variables will be updated iteratively until convergence with gradient descent based optimization algorithms.

Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian Approaches

no code implementations19 Apr 2019 Jiawei Zhang

One part of these algorithms will be introduced in this paper (including the Bayesian method and Lipschitzian approaches, e. g., Shubert-Piyavskii algorithm, Direct, LIPO and MCS), and the remaining algorithms (including the population based optimization algorithms, e. g., GA, SCE, DE, PSO, ES and CMA-ES, and random search algorithms, e. g., hill climbing and simulated annealing) will be introduced in the follow-up paper [18] in detail.

Derivative-Free Global Optimization Algorithms: Population based Methods and Random Search Approaches

no code implementations19 Apr 2019 Jiawei Zhang

This is a follow-up paper of [18], and we will introduce the population based optimization algorithms, e. g., GA, SCE, DE, PSO, ES and CMA-ES, and random search algorithms, e. g., hill climbing and simulated annealing, in this paper.

Missing Movie Synergistic Completion across Multiple Isomeric Online Movie Knowledge Libraries

no code implementations15 May 2019 Bowen Dong, Jiawei Zhang, Chenwei Zhang, Yang Yang, Philip S. Yu

Online knowledge libraries refer to the online data warehouses that systematically organize and categorize the knowledge-based information about different kinds of concepts and entities.

Secrets of the Brain: An Introduction to the Brain Anatomical Structure and Biological Function

no code implementations31 May 2019 Jiawei Zhang

In this paper, we will focus introducing the brain anatomical structure and biological function, as well as its surrounding sensory systems.

Cognitive Functions of the Brain: Perception, Attention and Memory

no code implementations30 May 2019 Jiawei Zhang

This is a follow-up tutorial article of [17] and [16], in this paper, we will introduce several important cognitive functions of the brain.

Decision Making

DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization

no code implementations25 Jul 2019 Jiyang Bai, Yuxiang Ren, Jiawei Zhang

Optimization algorithms with momentum, e. g., (ADAM), have been widely used for building deep learning models due to the faster convergence rates compared with stochastic gradient descent (SGD).

Stochastic Optimization

Graph Neural Networks for Small Graph and Giant Network Representation Learning: An Overview

no code implementations1 Aug 2019 Jiawei Zhang

Several different types of graph neural network models have been introduced for learning the representations from such different types of graphs already.

Graph Classification Representation Learning

BGADAM: Boosting based Genetic-Evolutionary ADAM for Neural Network Optimization

no code implementations26 Jul 2019 Jiyang Bai, Yuxiang Ren, Jiawei Zhang

To resolve this problem and further maximize the advantages of genetic algorithm with base learners, we propose to implement the boosting strategy for input model training, which can subsequently improve the effectiveness of genetic algorithm.

Is a Classification Procedure Good Enough? A Goodness-of-Fit Assessment Tool for Classification Learning

1 code implementation8 Nov 2019 Jiawei Zhang, Jie Ding, Yuhong Yang

For testing parametric classification models, the BAGofT has a broader scope than the existing methods since it is not restricted to specific parametric models (e. g., logistic regression).

Classification General Classification

EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph

no code implementations23 Dec 2019 Yuxiang Ren, Hao Zhu, Jiawei Zhang, Peng Dai, Liefeng Bo

Existing fraud detection methods try to identify unexpected dense subgraphs and treat related nodes as suspicious.

Fraud Detection

Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention

no code implementations5 Feb 2020 Yuxiang Ren, Jiawei Zhang

In addition, the experiment proved the expandability and generalizability of our for graph representation learning and other node classification related applications in heterogeneous graphs.

Fake News Detection Graph Attention +2

Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network

no code implementations17 Feb 2020 Jiyang Bai, Yuxiang Ren, Jiawei Zhang

To deal with these problems, in this paper, we propose a general subgraph-based training framework, namely Ripple Walk Training (RWT), for deep and large graph neural networks.

Attribute

Contaminant Removal for Android Malware Detection Systems

no code implementations7 Nov 2017 Lichao Sun, Xiaokai Wei, Jiawei Zhang, Lifang He, Philip S. Yu, Witawas Srisa-an

The results indicate that once we remove contaminants from the datasets, we can significantly improve both malware detection rate and detection accuracy

Cryptography and Security

CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection

no code implementations4 Apr 2020 Congying Xia, Chenwei Zhang, Hoang Nguyen, Jiawei Zhang, Philip Yu

In this paper, we formulate a more realistic and difficult problem setup for the intent detection task in natural language understanding, namely Generalized Few-Shot Intent Detection (GFSID).

Conditional Text Generation Intent Detection +3

G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning

no code implementations11 Jun 2020 Jiawei Zhang

In this paper, we will further investigate the graph-to-graph transfer of a universal GRAPH-BERT for graph representation learning across different graph datasets, and our proposed model is also referred to as the G5 for simplicity.

Classification Consistency Graph Representation Learning

EfficientFCN: Holistically-guided Decoding for Semantic Segmentation

no code implementations ECCV 2020 Jianbo Liu, Junjun He, Jiawei Zhang, Jimmy S. Ren, Hongsheng Li

State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (dilatedFCN), which adopt dilated convolutions in the backbone networks to extract high-resolution feature maps for achieving high-performance segmentation performance.

Segmentation Semantic Segmentation

Learning Event-Driven Video Deblurring and Interpolation

no code implementations ECCV 2020 Songnan Lin, Jiawei Zhang, Jinshan Pan, Zhe Jiang, Dongqing Zou, Yongtian Wang, Jing Chen, Jimmy Ren

Event-based sensors, which have a response if the change of pixel intensity exceeds a triggering threshold, can capture high-speed motion with microsecond accuracy.

Deblurring

OID: Outlier Identifying and Discarding in Blind Image Deblurring

no code implementations ECCV 2020 Liang Chen, Faming Fang, Jiawei Zhang, Jun Liu, Guixu Zhang

Even a small amount of outliers can dramatically degrade the quality of the estimated blur kernel, because the outliers are not conforming to the linear formation of the blurring process.

Blind Image Deblurring Image Deblurring

A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems

no code implementations NeurIPS 2020 Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhi-Quan Luo

We prove that the stabilized GDA algorithm can achieve an $O(1/\epsilon^2)$ iteration complexity for minimizing the pointwise maximum of a finite collection of nonconvex functions.

Distributed Stochastic Consensus Optimization with Momentum for Nonconvex Nonsmooth Problems

no code implementations10 Nov 2020 Zhiguo Wang, Jiawei Zhang, Tsung-Hui Chang, Jian Li, Zhi-Quan Luo

While many distributed optimization algorithms have been proposed for solving smooth or convex problems over the networks, few of them can handle non-convex and non-smooth problems.

Distributed Optimization

Search for the reaction $e^{+}e^{-} \rightarrow π^{+}π^{-} χ_{cJ}$ and a charmonium-like structure decaying to $χ_{cJ}π^{\pm}$ between 4.18 and 4.60 GeV

no code implementations4 Dec 2020 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, A. Amoroso, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X. L. Gao, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, T. T. Han, T. Z. Han, X. Q. Hao, F. A. Harris, N. Hüsken, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, D. Y. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, Y. F. Long, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. N. Ma, X. X. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, Q. Q. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, V. Thoren, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, Lei Zhang, S. Zhang, S. F. Zhang, T. J. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

We search for the process $e^{+}e^{-}\rightarrow \pi ^{+}\pi ^{-} \chi_{cJ}$ ($J=0, 1, 2$) and for a charged charmonium-like state in the $\pi ^{\pm} \chi_{cJ}$ subsystem.

High Energy Physics - Experiment

Online Stochastic Optimization with Wasserstein Based Non-stationarity

no code implementations13 Dec 2020 Jiashuo Jiang, Xiaocheng Li, Jiawei Zhang

We propose a unified Wasserstein-distance based measure to quantify the inaccuracy of the prior estimate in setting (i) and the non-stationarity of the system in setting (ii).

Management Stochastic Optimization

Systematic electrochemical etching of various metal tips for tunneling spectroscopy and scanning probe microscopy

no code implementations18 Jan 2021 Jiawei Zhang, Pinyuan Wang, Xuao Zhang, Haoran Ji, Jiawei Luo, He Wang, Jian Wang

To ensure the reproducibility of experimental results, the fabrication of tips should be standardized, and a controllable and convenient system should be set up.

Materials Science

Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection

no code implementations27 Jan 2021 Yuxiang Ren, Bo wang, Jiawei Zhang, Yi Chang

AA-HGNN utilizes an active learning framework to enhance learning performance, especially when facing the paucity of labeled data.

Active Learning Fake News Detection +2

ObjectAug: Object-level Data Augmentation for Semantic Image Segmentation

no code implementations30 Jan 2021 Jiawei Zhang, Yanchun Zhang, Xiaowei Xu

In addition, ObjectAug can support category-aware augmentation that gives various possibilities to objects in each category, and can be easily combined with existing image-level augmentation methods to further boost performance.

Data Augmentation Image Inpainting +4

Cross section measurement of $e^+e^- \to p\bar{p}η$ and $e^+e^- \to p\bar{p}ω$ at center-of-mass energies between 3.773 GeV and 4.6 GeV

no code implementations8 Feb 2021 M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N. Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, Lei Zhang, S. Zhang, S. F. Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

Based on $14. 7~\textrm{fb}^{-1}$ of $e^+e^-$ annihilation data collected with the BESIII detector at the BEPCII collider at 17 different center-of-mass energies between $3. 7730~\textrm{GeV}$ and $4. 5995~\textrm{GeV}$, Born cross sections of the two processes $e^+e^- \to p\bar{p}\eta$ and $e^+e^- \to p\bar{p}\omega$ are measured for the first time.

High Energy Physics - Experiment

Measurements of the center-of-mass energies of $e^{+}e^{-}$ collisions at BESIII

no code implementations29 Dec 2020 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, N Hüsken, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei LI, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

During the 2016-17 and 2018-19 running periods, the BESIII experiment collected 7. 5~fb$^{-1}$ of $e^+e^-$ collision data at center-of-mass energies ranging from 4. 13 to 4. 44 GeV.

High Energy Physics - Experiment

Model independent determination of the spin of the $Ω^{-}$ and its polarization alignment in $ψ(3686)\rightarrowΩ^{-}\barΩ^{+}$

no code implementations7 Jul 2020 M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, A. Amoroso, Q. An, Anita, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, J. V. Bennett, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J Biernat, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, J. P. Dai, X. C. Dai, A. Dbeyssi, R. B. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, S. X. Du, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, M. Fritsch, C. D. Fu, Y. Fu, X. L. Gao, Y. Gao, Y. G. Gao, I. Garzia, E. M. Gersabeck, A. Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, S. Han, T. T. Han, T. Z. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, T. Held, Y. K. Heng, M. Himmelreich, T. Holtmann, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, N. Huesken, T. Hussain, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, H. B. Jiang, X. S. Jiang, X. Y. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, L. Lavezzi, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, Ke Li, L. K. Li, Lei LI, P. L. Li, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, L. Z. Liao, J. Libby, C. X. Lin, B. Liu, B. J. Liu, C. X. Liu, D. Liu, D. Y. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. Y. Liu, K. Liu, K. Y. Liu, Ke Liu, L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, X. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, Y. F. Long, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. N. Ma, X. X. Ma, X. Y. Ma, Y. M. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, Q. A. Malik, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, A. Pitka, R. Poling, V. Prasad, H. Qi, H. R. Qi, M. Qi, T. Y. Qi, S. Qian, W. -B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, D. C. Shan, W. Shan, X. Y. Shan, M. Shao, C. P. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, Q. Q. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, F. F. Sui, G. X. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, V. Thoren, I. Uman, B. Wang, B. L. Wang, C. W. Wang, D. Y. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Y. J. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, X. A. Xiong, G. F. Xu, J. J. Xu, Q. J. Xu, W. Xu, X. P. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, R. X. Yang, S. L. Yang, Y. H. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, W. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, B. X. Zhang, Guangyi Zhang, H. H. Zhang, H. Y. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, T. J. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, W. J. Zhu, X. L. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

We present an analysis of the process $\psi(3686) \to \Omega^- \bar{\Omega}^+$ ($\Omega^-\to K^-\Lambda$, $\bar{\Omega}^+\to K^+\bar{\Lambda}$, $\Lambda\to p\pi^-$, $\bar{\Lambda}\to \bar{p}\pi^+$) based on a data set of $448\times 10^6$ $\psi(3686)$ decays collected with the BESIII detector at the BEPCII electron-positron collider.

High Energy Physics - Experiment

Measurement of the absolute branching fractions for purely leptonic $D_s^+$ decays

no code implementations23 Feb 2021 BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed, M. Albrecht, R. Aliberti, A. Amoroso, M. R. An, Q. An, X. H. Bai, Y. Bai, O. Bakina, R. Baldini Ferroli, I. Balossino, Y. Ban, K. Begzsuren, N. Berger, M. Bertani, D. Bettoni, F. Bianchi, J. Bloms, A. Bortone, I. Boyko, R. A. Briere, H. Cai, X. Cai, A. Calcaterra, G. F. Cao, N. Cao, S. A. Cetin, J. F. Chang, W. L. Chang, G. Chelkov, D. Y. Chen, G. Chen, H. S. Chen, M. L. Chen, S. J. Chen, X. R. Chen, Y. B. Chen, Z. J Chen, W. S. Cheng, G. Cibinetto, F. Cossio, X. F. Cui, H. L. Dai, X. C. Dai, A. Dbeyssi, R. E. de Boer, D. Dedovich, Z. Y. Deng, A. Denig, I. Denysenko, M. Destefanis, F. De Mori, Y. Ding, C. Dong, J. Dong, L. Y. Dong, M. Y. Dong, X. Dong, S. X. Du, Y. L. Fan, J. Fang, S. S. Fang, Y. Fang, R. Farinelli, L. Fava, F. Feldbauer, G. Felici, C. Q. Feng, J. H. Feng, M. Fritsch, C. D. Fu, Y. Gao, Y. G. Gao, I. Garzia, P. T. Ge, C. Geng, E. M. Gersabeck, A Gilman, K. Goetzen, L. Gong, W. X. Gong, W. Gradl, M. Greco, L. M. Gu, M. H. Gu, S. Gu, Y. T. Gu, C. Y Guan, A. Q. Guo, L. B. Guo, R. P. Guo, Y. P. Guo, A. Guskov, T. T. Han, W. Y. Han, X. Q. Hao, F. A. Harris, K. L. He, F. H. Heinsius, C. H. Heinz, T. Held, Y. K. Heng, C. Herold, M. Himmelreich, T. Holtmann, G. Y. Hou, Y. R. Hou, Z. L. Hou, H. M. Hu, J. F. Hu, T. Hu, Y. Hu, G. S. Huang, L. Q. Huang, X. T. Huang, Y. P. Huang, Z. Huang, T. Hussain, N Hüsken, W. Ikegami Andersson, W. Imoehl, M. Irshad, S. Jaeger, S. Janchiv, Q. Ji, Q. P. Ji, X. B. Ji, X. L. Ji, Y. Y. Ji, H. B. Jiang, X. S. Jiang, J. B. Jiao, Z. Jiao, S. Jin, Y. Jin, M. Q. Jing, T. Johansson, N. Kalantar-Nayestanaki, X. S. Kang, R. Kappert, M. Kavatsyuk, B. C. Ke, I. K. Keshk, A. Khoukaz, P. Kiese, R. Kiuchi, R. Kliemt, L. Koch, O. B. Kolcu, B. Kopf, M. Kuemmel, M. Kuessner, A. Kupsc, M. G. Kurth, W. Kühn, J. J. Lane, J. S. Lange, P. Larin, A. Lavania, L. Lavezzi, Z. H. Lei, H. Leithoff, M. Lellmann, T. Lenz, C. Li, C. H. Li, Cheng Li, D. M. Li, F. Li, G. Li, H. Li, H. B. Li, H. J. Li, J. L. Li, J. Q. Li, J. S. Li, Ke Li, L. K. Li, Lei LI, P. R. Li, S. Y. Li, W. D. Li, W. G. Li, X. H. Li, X. L. Li, Xiaoyu Li, Z. Y. Li, H. Liang, Y. F. Liang, Y. T. Liang, G. R. Liao, L. Z. Liao, J. Libby, C. X. Lin, B. J. Liu, C. X. Liu, D. Liu, F. H. Liu, Fang Liu, Feng Liu, H. B. Liu, H. M. Liu, Huanhuan Liu, Huihui Liu, J. B. Liu, J. L. Liu, J. Y. Liu, K. Liu, K. Y. Liu, L. Liu, M. H. Liu, P. L. Liu, Q. Liu, S. B. Liu, Shuai Liu, T. Liu, W. M. Liu, X. Liu, Y. Liu, Y. B. Liu, Z. A. Liu, Z. Q. Liu, X. C. Lou, F. X. Lu, H. J. Lu, J. D. Lu, J. G. Lu, X. L. Lu, Y. Lu, Y. P. Lu, C. L. Luo, M. X. Luo, P. W. Luo, T. Luo, X. L. Luo, S. Lusso, X. R. Lyu, F. C. Ma, H. L. Ma, L. L. Ma, M. M. Ma, Q. M. Ma, R. Q. Ma, R. T. Ma, X. X. Ma, X. Y. Ma, F. E. Maas, M. Maggiora, S. Maldaner, S. Malde, A. Mangoni, Y. J. Mao, Z. P. Mao, S. Marcello, Z. X. Meng, J. G. Messchendorp, G. Mezzadri, T. J. Min, R. E. Mitchell, X. H. Mo, Y. J. Mo, N. Yu. Muchnoi, H. Muramatsu, S. Nakhoul, Y. Nefedov, F. Nerling, I. B. Nikolaev, Z. Ning, S. Nisar, S. L. Olsen, Q. Ouyang, S. Pacetti, X. Pan, Y. Pan, A. Pathak, P. Patteri, M. Pelizaeus, H. P. Peng, K. Peters, J. Pettersson, J. L. Ping, R. G. Ping, R. Poling, V. Prasad, H. Qi, H. R. Qi, K. H. Qi, M. Qi, T. Y. Qi, S. Qian, W. B. Qian, Z. Qian, C. F. Qiao, L. Q. Qin, X. P. Qin, X. S. Qin, Z. H. Qin, J. F. Qiu, S. Q. Qu, K. H. Rashid, K. Ravindran, C. F. Redmer, A. Rivetti, V. Rodin, M. Rolo, G. Rong, Ch. Rosner, M. Rump, H. S. Sang, A. Sarantsev, Y. Schelhaas, C. Schnier, K. Schoenning, M. Scodeggio, D. C. Shan, W. Shan, X. Y. Shan, J. F. Shangguan, M. Shao, C. P. Shen, H. F. Shen, P. X. Shen, X. Y. Shen, H. C. Shi, R. S. Shi, X. Shi, X. D Shi, J. J. Song, W. M. Song, Y. X. Song, S. Sosio, S. Spataro, K. X. Su, P. P. Su, F. F. Sui, G. X. Sun, H. K. Sun, J. F. Sun, L. Sun, S. S. Sun, T. Sun, W. Y. Sun, X Sun, Y. J. Sun, Y. K. Sun, Y. Z. Sun, Z. T. Sun, Y. H. Tan, Y. X. Tan, C. J. Tang, G. Y. Tang, J. Tang, J. X. Teng, V. Thoren, W. H. Tian, Y. T. Tian, I. Uman, B. Wang, C. W. Wang, D. Y. Wang, H. J. Wang, H. P. Wang, K. Wang, L. L. Wang, M. Wang, M. Z. Wang, Meng Wang, W. Wang, W. H. Wang, W. P. Wang, X. Wang, X. F. Wang, X. L. Wang, Y. Wang, Y. D. Wang, Y. F. Wang, Y. Q. Wang, Y. Y. Wang, Z. Wang, Z. Y. Wang, Ziyi Wang, Zongyuan Wang, D. H. Wei, P. Weidenkaff, F. Weidner, S. P. Wen, D. J. White, U. Wiedner, G. Wilkinson, M. Wolke, L. Wollenberg, J. F. Wu, L. H. Wu, L. J. Wu, X. Wu, Z. Wu, L. Xia, H. Xiao, S. Y. Xiao, Z. J. Xiao, X. H. Xie, Y. G. Xie, Y. H. Xie, T. Y. Xing, G. F. Xu, Q. J. Xu, W. Xu, X. P. Xu, Y. C. Xu, F. Yan, L. Yan, W. B. Yan, W. C. Yan, Xu Yan, H. J. Yang, H. X. Yang, L. Yang, S. L. Yang, Y. X. Yang, Yifan Yang, Zhi Yang, M. Ye, M. H. Ye, J. H. Yin, Z. Y. You, B. X. Yu, C. X. Yu, G. Yu, J. S. Yu, T. Yu, C. Z. Yuan, L. Yuan, X. Q. Yuan, Y. Yuan, Z. Y. Yuan, C. X. Yue, A. Yuncu, A. A. Zafar, Y. Zeng, A. Q. Zhang, B. X. Zhang, Guangyi Zhang, H. Zhang, H. H. Zhang, H. Y. Zhang, J. J. Zhang, J. L. Zhang, J. Q. Zhang, J. W. Zhang, J. Y. Zhang, J. Z. Zhang, Jianyu Zhang, Jiawei Zhang, L. M. Zhang, L. Q. Zhang, Lei Zhang, S. Zhang, S. F. Zhang, Shulei Zhang, X. D. Zhang, X. Y. Zhang, Y. Zhang, Y. H. Zhang, Y. T. Zhang, Yan Zhang, Yao Zhang, Yi Zhang, Z. H. Zhang, Z. Y. Zhang, G. Zhao, J. Zhao, J. Y. Zhao, J. Z. Zhao, Lei Zhao, Ling Zhao, M. G. Zhao, Q. Zhao, S. J. Zhao, Y. B. Zhao, Y. X. Zhao, Z. G. Zhao, A. Zhemchugov, B. Zheng, J. P. Zheng, Y. Zheng, Y. H. Zheng, B. Zhong, C. Zhong, L. P. Zhou, Q. Zhou, X. Zhou, X. K. Zhou, X. R. Zhou, X. Y. Zhou, A. N. Zhu, J. Zhu, K. Zhu, K. J. Zhu, S. H. Zhu, T. J. Zhu, W. J. Zhu, Y. C. Zhu, Z. A. Zhu, B. S. Zou, J. H. Zou

Constraining our measurement to the Standard Model expectation of lepton universality ($R=9. 75$), we find the more precise results $\cal B(D_s^+\to \tau^+\nu_\tau) = (5. 22\pm0. 10\pm 0. 14)\times10^{-2}$ and $A_{\it CP}(\tau^\pm\nu_\tau) = (-0. 1\pm1. 9\pm1. 0)\%$.

High Energy Physics - Experiment

Topology Learning Aided False Data Injection Attack without Prior Topology Information

no code implementations24 Feb 2021 Martin Higgins, Jiawei Zhang, Ning Zhang, Fei Teng

False Data Injection (FDI) attacks against powersystem state estimation are a growing concern for operators. Previously, most works on FDI attacks have been performedunder the assumption of the attacker having full knowledge ofthe underlying system without clear justification.

Efficient Deep Image Denoising via Class Specific Convolution

no code implementations2 Mar 2021 Lu Xu, Jiawei Zhang, Xuanye Cheng, Feng Zhang, Xing Wei, Jimmy Ren

In this paper, we propose an efficient deep neural network for image denoising based on pixel-wise classification.

Image Denoising

Decentralized Non-Convex Learning with Linearly Coupled Constraints

no code implementations9 Mar 2021 Jiawei Zhang, Songyang Ge, Tsung-Hui Chang, Zhi-Quan Luo

Motivated by the need for decentralized learning, this paper aims at designing a distributed algorithm for solving nonconvex problems with general linear constraints over a multi-agent network.

Optimization and Control Systems and Control Systems and Control

Centrality Meets Centroid: A Graph-based Approach for Unsupervised Document Summarization

no code implementations29 Mar 2021 Haopeng Zhang, Jiawei Zhang

Unsupervised document summarization has re-acquired lots of attention in recent years thanks to its simplicity and data independence.

Document Summarization Extractive Document Summarization +1

Pyramid U-Net for Retinal Vessel Segmentation

no code implementations6 Apr 2021 Jiawei Zhang, Yanchun Zhang, Xiaowei Xu

To further improve performance, two optimizations including pyramid inputs enhancement and deep pyramid supervision are applied to PSABs in the encoder and decoder, respectively.

Retinal Vessel Segmentation Segmentation

Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs

no code implementations6 Apr 2021 Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu

To model the uncertainty, we devise a hyperbolic graph variational autoencoder built upon the proposed TGNN to generate stochastic node representations of hyperbolic normal distributions.

A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approaches

no code implementations7 May 2021 Pingli Ma, Chen Li, Md Mamunur Rahaman, YuDong Yao, Jiawei Zhang, Shuojia Zou, Xin Zhao, Marcin Grzegorzek

In this review, first, we analyse the existing microorganism detection methods in chronological order, from traditional image processing and traditional machine learning to deep learning methods.

object-detection Object Detection

Drill the Cork of Information Bottleneck by Inputting the Most Important Data

no code implementations15 May 2021 Xinyu Peng, Jiawei Zhang, Fei-Yue Wang, Li Li

As a promising tool to better understand the learning dynamic of minibatch SGD, the information bottleneck (IB) theory claims that the optimization process consists of an initial fitting phase and the following compression phase.

EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis

no code implementations18 May 2021 Tianchen Wang, Zhihe Li, Meiping Huang, Jian Zhuang, Shanshan Bi, Jiawei Zhang, Yiyu Shi, Hongwen Fei, Xiaowei Xu

For PFO diagnosis, contrast transthoracic echocardiography (cTTE) is preferred as being a more robust method compared with others.

Blind Deblurring for Saturated Images

no code implementations CVPR 2021 Liang Chen, Jiawei Zhang, Songnan Lin, Faming Fang, Jimmy S. Ren

To address this problem, we introduce a new blur model to fit both saturated and unsaturated pixels, and all informative pixels can be considered during deblurring process.

Deblurring

Learning a Non-Blind Deblurring Network for Night Blurry Images

no code implementations CVPR 2021 Liang Chen, Jiawei Zhang, Jinshan Pan, Songnan Lin, Faming Fang, Jimmy S. Ren

Deblurring night blurry images is difficult, because the common-used blur model based on the linear convolution operation does not hold in this situation due to the influence of saturated pixels.

Deblurring Image Restoration

Targeted Cross-Validation

no code implementations14 Sep 2021 Jiawei Zhang, Jie Ding, Yuhong Yang

A standard approach is to find the globally best modeling method from a set of candidate methods.

Learning To Know Where To See: A Visibility-Aware Approach for Occluded Person Re-Identification

no code implementations ICCV 2021 Jinrui Yang, Jiawei Zhang, Fufu Yu, Xinyang Jiang, Mengdan Zhang, Xing Sun, Ying-Cong Chen, Wei-Shi Zheng

Several mainstream methods utilize extra cues (e. g., human pose information) to distinguish human parts from obstacles to alleviate the occlusion problem.

Person Re-Identification

CARD: Certifiably Robust Machine Learning Pipeline via Domain Knowledge Integration

no code implementations29 Sep 2021 Jiawei Zhang, Linyi Li, Bo Li

In particular, we express the domain knowledge as first-order logic rules and embed these logic rules in a probabilistic graphical model.

BIG-bench Machine Learning

A Multi-Task Learning Algorithm for Non-personalized Recommendations

no code implementations29 Sep 2021 Jiawei Zhang

In this paper, we introduce a multi-task learning (MTL) algorithm for recommending non-personalized videos to watch next on industrial video sharing platforms.

Collaborative Filtering Multi-Task Learning +1

EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation

no code implementations11 Oct 2021 Hechen Yang, Chen Li, Xin Zhao, Bencheng Cai, Jiawei Zhang, Pingli Ma, Peng Zhao, Ao Chen, Hongzan Sun, Yueyang Teng, Shouliang Qi, Tao Jiang, Marcin Grzegorzek

The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corresponding object labeling files in ". XML" format file.

Object object-detection +1

Collaborative Graph Contrastive Learning: Data Augmentation Composition May Not be Necessary for Graph Representation Learning

no code implementations5 Nov 2021 Yuxiang Ren, Jiawei Zhang

Extensive experiments demonstrate the advantages of CGCL in unsupervised graph representation learning and the non-necessity of handcrafted data augmentation composition for graph representation learning.

Contrastive Learning Data Augmentation +2

Doubly Optimal No-Regret Online Learning in Strongly Monotone Games with Bandit Feedback

no code implementations6 Dec 2021 Tianyi Lin, Zhengyuan Zhou, Wenjia Ba, Jiawei Zhang

Leveraging self-concordant barrier functions, we first construct a new bandit learning algorithm and show that it achieves the single-agent optimal regret of $\tilde{\Theta}(n\sqrt{T})$ under smooth and strongly concave reward functions ($n \geq 1$ is the problem dimension).

A Self-supervised Mixed-curvature Graph Neural Network

no code implementations10 Dec 2021 Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu

Instead of working on one single constant-curvature space, we construct a mixed-curvature space via the Cartesian product of multiple Riemannian component spaces and design hierarchical attention mechanisms for learning and fusing the representations across these component spaces.

Contrastive Learning Graph Representation Learning

Measuring and Sampling: A Metric-guided Subgraph Learning Framework for Graph Neural Network

no code implementations30 Dec 2021 Jiyang Bai, Yuxiang Ren, Jiawei Zhang

We demonstrate the effectiveness and efficiency of MeGuide in training various GNNs on multiple datasets.

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

no code implementations18 Feb 2022 Jiawei Zhang, Chen Li, Md Mamunur Rahaman, YuDong Yao, Pingli Ma, Jinghua Zhang, Xin Zhao, Tao Jiang, Marcin Grzegorzek

This study has high research significance and application value, which can be referred to microbial researchers to have a comprehensive understanding of microorganism biovolume measurements using digital image analysis methods and potential applications.

Image Segmentation Semantic Segmentation

Learning to Order for Inventory Systems with Lost Sales and Uncertain Supplies

no code implementations10 Jul 2022 Boxiao Chen, Jiashuo Jiang, Jiawei Zhang, Zhengyuan Zhou

We aim to minimize the $T$-period cost, a problem that is known to be computationally intractable even under known distributions of demand and supply.

Degeneracy is OK: Logarithmic Regret for Network Revenue Management with Indiscrete Distributions

no code implementations14 Oct 2022 Jiashuo Jiang, Will Ma, Jiawei Zhang

We study the classical Network Revenue Management (NRM) problem with accept/reject decisions and $T$ IID arrivals.

Management

When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work

no code implementations NeurIPS 2021 Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo

Third, we consider a constrained optimization formulation where the feasible region is the nice local region, and prove that every KKT point is a nearly global minimizer.

Self-Supervised Intensity-Event Stereo Matching

no code implementations1 Nov 2022 Jinjin Gu, Jinan Zhou, Ringo Sai Wo Chu, Yan Chen, Jiawei Zhang, Xuanye Cheng, Song Zhang, Jimmy S. Ren

Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes in microsecond accuracy with a high dynamic range and low power consumption.

Self-Supervised Learning Stereo Matching

Robot Basics: Representation, Rotation and Velocity

no code implementations5 Nov 2022 Jiawei Zhang

In this article, we plan to provide an introduction about some basics about robots for readers.

Motion Planning

Coordinating CAV Swarms at Intersections with a Deep Learning Model

no code implementations10 Nov 2022 Jiawei Zhang, Shen Li, Li Li

Connected and automated vehicles (CAVs) are viewed as a special kind of robots that have the potential to significantly improve the safety and efficiency of traffic.

Scheduling

Robot Kinematics: Motion, Kinematics and Dynamics

no code implementations28 Nov 2022 Jiawei Zhang

As to some more advanced topics about robot control, we will introduce them in the following tutorial articles for readers instead.

Math

Mutimodal Ranking Optimization for Heterogeneous Face Re-identification

no code implementations11 Dec 2022 Hui Hu, Jiawei Zhang, Zhen Han

Secondly, we propose linear and non-linear fusion strategies to aggregate initial ranking lists of multimodal face pairs and acquire the optimized re-ranked list based on modal complementarity.

Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation

no code implementations28 Dec 2022 Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

Offline reinforcement learning (RL) aims to find an optimal policy for sequential decision-making using a pre-collected dataset, without further interaction with the environment.

Decision Making Offline RL +1

Deep Dynamic Scene Deblurring from Optical Flow

no code implementations18 Jan 2023 Jiawei Zhang, Jinshan Pan, Daoye Wang, Shangchen Zhou, Xing Wei, Furong Zhao, Jianbo Liu, Jimmy Ren

In this paper, we explore optical flow to remove dynamic scene blur by using the multi-scale spatially variant recurrent neural network (RNN).

Deblurring Optical Flow Estimation

Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise

no code implementations14 Feb 2023 Zijian Liu, Jiawei Zhang, Zhengyuan Zhou

For this class of problems, we propose the first variance-reduced accelerated algorithm and establish that it guarantees a high-probability convergence rate of $O(\log(T/\delta)T^{\frac{1-p}{2p-1}})$ under a mild condition, which is faster than $\Omega(T^{\frac{1-p}{3p-2}})$.

Stochastic Optimization

Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the Generation of Adversarial Examples

no code implementations8 Mar 2023 Jinwei Wang, Hao Wu, Haihua Wang, Jiawei Zhang, Xiangyang Luo, Bin Ma

Therefore, we propose a novel adversarial defense mechanism, which is referred to as immune defense and is the example-based pre-defense.

Adversarial Defense

Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System

no code implementations25 Mar 2023 Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, Jiawei Zhang

Large language models (LLMs) have demonstrated their significant potential to be applied for addressing various application tasks.

In-Context Learning Recommendation Systems

AMC-Net: An Effective Network for Automatic Modulation Classification

no code implementations2 Apr 2023 Jiawei Zhang, Tiantian Wang, Zhixi Feng, Shuyuan Yang

Automatic modulation classification (AMC) is a crucial stage in the spectrum management, signal monitoring, and control of wireless communication systems.

Classification Denoising +2

Extractive Summarization via ChatGPT for Faithful Summary Generation

no code implementations9 Apr 2023 Haopeng Zhang, Xiao Liu, Jiawei Zhang

In addition, we explore the effectiveness of in-context learning and chain-of-thought reasoning for enhancing its performance.

Extractive Summarization In-Context Learning +1

SummIt: Iterative Text Summarization via ChatGPT

no code implementations24 May 2023 Haopeng Zhang, Xiao Liu, Jiawei Zhang

Text summarization systems have made significant progress in recent years, but typically generate summaries in one single step.

Text Summarization

Generic Attention-model Explainability by Weighted Relevance Accumulation

no code implementations20 Aug 2023 Yiming Huang, Aozhe Jia, Xiaodan Zhang, Jiawei Zhang

In this paper, we propose a weighted relevancy strategy, which takes the importance of token values into consideration, to reduce distortion when equally accumulating relevance.

Image Captioning Question Answering +1

iLoRE: Dynamic Graph Representation with Instant Long-term Modeling and Re-occurrence Preservation

no code implementations5 Sep 2023 Siwei Zhang, Yun Xiong, Yao Zhang, Xixi Wu, Yiheng Sun, Jiawei Zhang

To overcome the indiscriminate updating issue, we introduce the Adaptive Short-term Updater module that will automatically discard the useless or noisy edges, ensuring iLoRE's effectiveness and instant ability.

Fraud Detection Representation Learning

Unsupervised Multi-document Summarization with Holistic Inference

no code implementations8 Sep 2023 Haopeng Zhang, Sangwoo Cho, Kaiqiang Song, Xiaoyang Wang, Hongwei Wang, Jiawei Zhang, Dong Yu

SRI balances the importance and diversity of a subset of sentences from the source documents and can be calculated in unsupervised and adaptive manners.

Document Summarization Extractive Summarization +1

A Health Monitoring System Based on Flexible Triboelectric Sensors for Intelligence Medical Internet of Things and its Applications in Virtual Reality

no code implementations13 Sep 2023 Junqi Mao, Puen Zhou, Xiaoyao Wang, Hongbo Yao, Liuyang Liang, Yiqiao Zhao, Jiawei Zhang, Dayan Ban, Haiwu Zheng

The Internet of Medical Things (IoMT) is a platform that combines Internet of Things (IoT) technology with medical applications, enabling the realization of precision medicine, intelligent healthcare, and telemedicine in the era of digitalization and intelligence.

Driving behavior-guided battery health monitoring for electric vehicles using machine learning

no code implementations25 Sep 2023 Nanhua Jiang, Jiawei Zhang, Weiran Jiang, Yao Ren, Jing Lin, Edwin Khoo, Ziyou Song

To address these issues, we proposed a feature-based machine learning pipeline for reliable battery health monitoring, enabled by evaluating the acquisition probability of features under real-world driving conditions.

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization

no code implementations2 Nov 2023 Wei Shen, Minhui Huang, Jiawei Zhang, Cong Shen

In recent years, federated minimax optimization has attracted growing interest due to its extensive applications in various machine learning tasks.

Federated Learning

3DifFusionDet: Diffusion Model for 3D Object Detection with Robust LiDAR-Camera Fusion

no code implementations7 Nov 2023 Xinhao Xiang, Simon Dräger, Jiawei Zhang

We propose the 3DifFusionDet framework in this paper, which structures 3D object detection as a denoising diffusion process from noisy 3D boxes to target boxes.

3D Object Detection Denoising +2

FusionViT: Hierarchical 3D Object Detection via LiDAR-Camera Vision Transformer Fusion

no code implementations7 Nov 2023 Xinhao Xiang, Jiawei Zhang

Different from the existing 3D object detection approaches, FusionViT is a pure-ViT based framework, which adopts a hierarchical architecture by extending the transformer model to embed both images and point clouds for effective representation learning.

3D Object Detection Object +3

Beyond Text: Unveiling Multimodal Proficiency of Large Language Models with MultiAPI Benchmark

1 code implementation21 Nov 2023 Xiao Liu, Jianfeng Lin, Jiawei Zhang

The proliferation of Large Language Models like ChatGPT has significantly advanced language understanding and generation, impacting a broad spectrum of applications.

Decision Making

Diffusion-based Blind Text Image Super-Resolution

no code implementations13 Dec 2023 Yuzhe Zhang, Jiawei Zhang, Hao Li, Zhouxia Wang, Luwei Hou, Dongqing Zou, Liheng Bian

Since text prior is important to guarantee the correctness of the restored text structure according to existing arts, we also propose a Text Diffusion Model (TDM) for text recognition which can guide IDM to generate text images with correct structures.

Image Generation Image Super-Resolution

A Revisit of Fake News Dataset with Augmented Fact-checking by ChatGPT

no code implementations19 Dec 2023 Zizhong Li, Haopeng Zhang, Jiawei Zhang

The proliferation of fake news has emerged as a critical issue in recent years, requiring significant efforts to detect it.

Fact Checking Fake News Detection

Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces

no code implementations2 Jan 2024 Li Sun, Junda Ye, Jiawei Zhang, Yong Yang, Mingsheng Liu, Feiyang Wang, Philip S. Yu

To address the aforementioned issues, we propose a novel Contrastive model for Sequential Interaction Network learning on Co-Evolving RiEmannian spaces, CSINCERE.

Contrastive Learning Recommendation Systems

EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector

no code implementations3 Jan 2024 Jiawei Zhang, Yufan Chen, Cheng Jin, Lei Zhu, Yuantao Gu

Out-of-distribution (OOD) detection plays a crucial role in ensuring the security of neural networks.

Out of Distribution (OOD) Detection

Generalized Lagrangian Neural Networks

no code implementations8 Jan 2024 Shanshan Xiao, Jiawei Zhang, Yifa Tang

Then in this article, we introduce a groundbreaking extension (Genralized Lagrangian Neural Networks) to Lagrangian Neural Networks (LNNs), innovatively tailoring them for non-conservative systems.

Bias-Compensated State of Charge and State of Health Joint Estimation for Lithium Iron Phosphate Batteries

no code implementations16 Jan 2024 Baozhao Yi, Xinhao Du, Jiawei Zhang, Xiaogang Wu, Qiuhao Hu, Weiran Jiang, Xiaosong Hu, Ziyou Song

Besides, the voltage measurement biases estimated in the low-slope SOC regions are compensated in the following joint estimation of SOC and SOH to enhance the state estimation accuracy further.

Cyclic Neural Network

no code implementations11 Jan 2024 Liangwei Yang, Hengrui Zhang, Zihe Song, Jiawei Zhang, Weizhi Zhang, Jing Ma, Philip S. Yu

This paper answers a fundamental question in artificial neural network (ANN) design: We do not need to build ANNs layer-by-layer sequentially to guarantee the Directed Acyclic Graph (DAG) property.

Prompt Learning on Temporal Interaction Graphs

no code implementations9 Feb 2024 Xi Chen, Siwei Zhang, Yun Xiong, Xixi Wu, Jiawei Zhang, Xiangguo Sun, Yao Zhang, Feng Zhao, Yulin kang

In detail, we propose a temporal prompt generator to offer temporally-aware prompts for different tasks.

Representation Learning

DDIPrompt: Drug-Drug Interaction Event Prediction based on Graph Prompt Learning

no code implementations18 Feb 2024 Yingying Wang, Yun Xiong, Xixi Wu, Xiangguo Sun, Jiawei Zhang

(2) the scarcity of labeled data for rare events, which is a pervasive issue in the medical field where rare yet potentially critical interactions are often overlooked or under-studied due to limited available data.

Unveiling the Magic: Investigating Attention Distillation in Retrieval-augmented Generation

no code implementations19 Feb 2024 Zizhong Li, Haopeng Zhang, Jiawei Zhang

Retrieval-augmented generation framework can address the limitations of large language models by enabling real-time knowledge updates for more accurate answers.

Retrieval

MuseGraph: Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Mining

no code implementations2 Mar 2024 Yanchao Tan, Hang Lv, Xinyi Huang, Jiawei Zhang, Shiping Wang, Carl Yang

Traditional Graph Neural Networks (GNNs), which are commonly used for modeling attributed graphs, need to be re-trained every time when applied to different graph tasks and datasets.

Graph Mining

Regulating Chatbot Output via Inter-Informational Competition

no code implementations17 Mar 2024 Jiawei Zhang

In fact, a trove of empirical evidence has demonstrated that market competition among information outlets can effectively mitigate most risks and that overreliance on regulation is not only unnecessary but detrimental, as well.

Chatbot

EffiPerception: an Efficient Framework for Various Perception Tasks

no code implementations18 Mar 2024 Xinhao Xiang, Simon Dräger, Jiawei Zhang

The accuracy-speed-memory trade-off is always the priority to consider for several computer vision perception tasks.

3D Object Detection Data Augmentation +5

VersaT2I: Improving Text-to-Image Models with Versatile Reward

no code implementations27 Mar 2024 Jianshu Guo, Wenhao Chai, Jie Deng, Hsiang-Wei Huang, Tian Ye, Yichen Xu, Jiawei Zhang, Jenq-Neng Hwang, Gaoang Wang

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance.

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