Search Results for author: Li Wang

Found 163 papers, 25 papers with code

Multilevel Perception Boundary-guided Network for Breast Lesion Segmentation in Ultrasound Images

no code implementations23 Oct 2023 Xing Yang, Jian Zhang, Qijian Chen, Li Wang, Lihui Wang

Moreover, to improve the segmentation performance for tumor boundaries, a multi-level boundary-enhanced segmentation (BS) loss is proposed.

Lesion Segmentation Segmentation +1

Fuzzy-NMS: Improving 3D Object Detection with Fuzzy Classification in NMS

no code implementations21 Oct 2023 Li Wang, Xinyu Zhang, Fachuan Zhao, Chuze Wu, Yichen Wang, Ziying Song, Lei Yang, Jun Li, Huaping Liu

The proposed Fuzzy-NMS module combines the volume and clustering density of candidate bounding boxes, refining them with a fuzzy classification method and optimizing the appropriate suppression thresholds to reduce uncertainty in the NMS process.

3D Object Detection object-detection

Progressive Dual Priori Network for Generalized Breast Tumor Segmentation

no code implementations20 Oct 2023 Li Wang, Lihui Wang, Zixiang Kuai, Lei Tang, Yingfeng Ou, Chen Ye, Yuemin Zhu

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast amd irregular shape, we propose a progressive dual priori network (PDPNet) to segment breast tumors from dynamic enhanced magnetic resonance images (DCE-MRI) acquired at different sites.

Segmentation Tumor Segmentation

FMRT: Learning Accurate Feature Matching with Reconciliatory Transformer

no code implementations20 Oct 2023 Xinyu Zhang, Li Wang, Zhiqiang Jiang, Kun Dai, Tao Xie, Lei Yang, Wenhao Yu, Yang shen, Jun Li

However, these methods only integrate long-range context information among keypoints with a fixed receptive field, which constrains the network from reconciling the importance of features with different receptive fields to realize complete image perception, hence limiting the matching accuracy.

Homography Estimation Pose Estimation +1

Dual Radar: A Multi-modal Dataset with Dual 4D Radar for Autonomous Driving

1 code implementation11 Oct 2023 Xinyu Zhang, Li Wang, Jian Chen, Cheng Fang, Lei Yang, Ziying Song, Guangqi Yang, Yichen Wang, Xiaofei Zhang, Jun Li, Zhiwei Li, Qingshan Yang, Zhenlin Zhang, Shuzhi Sam Ge

Compared with commonly used 3D radars, the latest 4D radars have precise vertical resolution and higher point cloud density, making it a highly promising sensor for autonomous driving in complex environmental perception.

3D Object Detection Autonomous Driving +1

MonoGAE: Roadside Monocular 3D Object Detection with Ground-Aware Embeddings

no code implementations30 Sep 2023 Lei Yang, Jiaxin Yu, Xinyu Zhang, Jun Li, Li Wang, Yi Huang, Chuang Zhang, Hong Wang, Yiming Li

We discover that most existing monocular 3D object detectors rely on the ego-vehicle prior assumption that the optical axis of the camera is parallel to the ground.

Autonomous Driving Monocular 3D Object Detection +1

BEVHeight++: Toward Robust Visual Centric 3D Object Detection

no code implementations28 Sep 2023 Lei Yang, Tao Tang, Jun Li, Peng Chen, Kun Yuan, Li Wang, Yi Huang, Xinyu Zhang, Kaicheng Yu

In essence, we regress the height to the ground to achieve a distance-agnostic formulation to ease the optimization process of camera-only perception methods.

3D Object Detection Autonomous Driving +1

DeepAdaIn-Net: Deep Adaptive Device-Edge Collaborative Inference for Augmented Reality

no code implementations IEEE Journal of Selected Topics in Signal Processing 2023 Li Wang, Xin Wu, Yi Zhang, Xinyun Zhang, LianmingXu, Zhihua Wu, Aiguo Fei

Specifically, DeepAdaIn-Net encompasses a partition point selection (PPS) module, a high feature compression learning (HFCL) module, a bandwidth-aware feature configuration (BaFC) module, and a feature consistency compensation (FCC) module.

Collaborative Inference Feature Compression +1

Exploring the Influence of Information Entropy Change in Learning Systems

no code implementations19 Sep 2023 Xiaowei Yu, Yao Xue, Lu Zhang, Li Wang, Tianming Liu, Dajiang Zhu

We theoretically prove the enhancement gained from positive noise by reducing the task complexity defined by information entropy and experimentally show the significant performance gain in large image datasets, such as the ImageNet.

Image Classification Transfer Learning

A Stochastic Online Forecast-and-Optimize Framework for Real-Time Energy Dispatch in Virtual Power Plants under Uncertainty

no code implementations15 Sep 2023 Wei Jiang, Zhongkai Yi, Li Wang, Hanwei Zhang, Jihai Zhang, Fangquan Lin, Cheng Yang

Aggregating distributed energy resources in power systems significantly increases uncertainties, in particular caused by the fluctuation of renewable energy generation.

Data Augmentation energy management +2

Deep Learning and Bayesian inference for Inverse Problems

no code implementations28 Aug 2023 Ali Mohammad-Djafari, Ning Chu, Li Wang, Liang Yu

However, accounting for the uncertainties, we need first understand the Bayesian Deep Learning and then, we can see how we can use them for inverse problems.

Bayesian Inference

Early Autism Diagnosis based on Path Signature and Siamese Unsupervised Feature Compressor

no code implementations12 Jul 2023 Zhuowen Yin, Xinyao Ding, Xin Zhang, Zhengwang Wu, Li Wang, Gang Li

Given evidences of neurodevelopmental abnormalities in ASD infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis.

Brain Anatomy Prior Modeling to Forecast Clinical Progression of Cognitive Impairment with Structural MRI

no code implementations20 Jun 2023 Lintao Zhang, Jinjian Wu, Lihong Wang, Li Wang, David C. Steffens, Shijun Qiu, Guy G. Potter, Mingxia Liu

Besides the encoder, the pretext model also contains two decoders for two auxiliary tasks (i. e., MRI reconstruction and brain tissue segmentation), while the downstream model relies on a predictor for classification.

Anatomy MRI Reconstruction +1

Testing for intrinsic multifractality in the global grain spot market indices: A multifractal detrended fluctuation analysis

no code implementations18 Jun 2023 Li Wang, Xing-Lu Gao, Wei-Xing Zhou

Extensive statistical tests confirm the presence of intrinsic multifractality in the maize and barley sub-indices and the absence of intrinsic multifractality in the wheat and rice sub-indices.

Option pricing under jump diffusion model

no code implementations18 May 2023 Qian Li, Li Wang

We provide an European option pricing formula written in the form of an infinite series of Black Scholes type terms under double Levy jumps model, where both the interest rate and underlying price are driven by Levy process.

NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering

no code implementations CVPR 2023 Yu-Tao Liu, Li Wang, Jie Yang, Weikai Chen, Xiaoxu Meng, Bo Yang, Lin Gao

Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering.

Neural Rendering Surface Reconstruction +1

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

1 code implementation CVPR 2023 Lei Yang, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen

In essence, instead of predicting the pixel-wise depth, we regress the height to the ground to achieve a distance-agnostic formulation to ease the optimization process of camera-only perception methods.

3D Object Detection Autonomous Driving +1

BERT-ERC: Fine-tuning BERT is Enough for Emotion Recognition in Conversation

no code implementations17 Jan 2023 Xiangyu Qin, Zhiyu Wu, Jinshi Cui, Tingting Zhang, Yanran Li, Jian Luan, Bin Wang, Li Wang

Accordingly, we propose a novel paradigm, i. e., exploring contextual information and dialogue structure information in the fine-tuning step, and adapting the PLM to the ERC task in terms of input text, classification structure, and training strategy.

Emotion Recognition in Conversation text-classification +1

CO-Net: Learning Multiple Point Cloud Tasks at Once with A Cohesive Network

no code implementations ICCV 2023 Tao Xie, Ke Wang, Siyi Lu, Yukun Zhang, Kun Dai, Xiaoyu Li, Jie Xu, Li Wang, Lijun Zhao, Xinyu Zhang, Ruifeng Li

Finally, we propose a sign-based gradient surgery to promote the training of CO-Net, thereby emphasizing the usage of task-shared parameters and guaranteeing that each task can be thoroughly optimized.

Incremental Learning Multi-Task Learning

Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations

1 code implementation9 Dec 2022 Wuzhe Xu, Yulong Lu, Li Wang

Deep operator network (DeepONet) has demonstrated great success in various learning tasks, including learning solution operators of partial differential equations.

Transfer Learning

Superimposed Pilot-based Channel Estimation for RIS-Assisted IoT Systems Using Lightweight Networks

no code implementations7 Dec 2022 Chaojin Qing, Li Wang, Lei Dong, Guowei Ling, Jiafan Wang

Specifically, at the user equipment (UE), the pilot for CE is superimposed on the uplink user data to improve the spectral efficiency and energy consumption for IoT systems, and two lightweight networks at the base station (BS) alleviate the computational complexity and processing delay for the CE and symbol detection (SD).

Machine Learning-based Methods for Reconfigurable Antenna Mode Selection in MIMO Systems

no code implementations24 Nov 2022 Yasaman Abdollahian, Ehsan Tohidi, Martin Kasparick, Li Wang, Ahmet Hasim Gokceoglu, Slawomir Stanczak

Due to the non-convexity of this problem, we propose machine learning-based methods for RA antenna mode selection in both dynamic and static scenarios.

Deep Factorization Model for Robust Recommendation

no code implementations5 Nov 2022 Li Wang, Qiang Zhao, Wei Wang

Recently, malevolent user hacking has become a huge problem for real-world companies.

Recommendation Systems

CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

no code implementations6 Sep 2022 Li Wang, Xinyu Zhang, Wenyuan Qin, Xiaoyu Li, Lei Yang, Zhiwei Li, Lei Zhu, Hong Wang, Jun Li, Huaping Liu

As such, we propose a novel camera-LiDAR fusion 3D MOT framework based on the Combined Appearance-Motion Optimization (CAMO-MOT), which uses both camera and LiDAR data and significantly reduces tracking failures caused by occlusion and false detection.

3D Multi-Object Tracking Autonomous Driving +1

Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy

no code implementations18 Aug 2022 Wenqiang Ruan, Mingxin Xu, Wenjing Fang, Li Wang, Lei Wang, Weili Han

Second, to reduce the accuracy loss led by differential privacy noise and the huge communication overhead of MPL, we propose two optimization methods for the training process of MPL: (1) the data-independent feature extraction method, which aims to simplify the trained model structure; (2) the local data-based global model initialization method, which aims to speed up the convergence of the model training.

Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network

no code implementations9 Aug 2022 Yunzhi Huang, Sahar Ahmad, Luyi Han, Shuai Wang, Zhengwang Wu, Weili Lin, Gang Li, Li Wang, Pew-Thian Yap

In this paper, we propose a deep learning framework to predict missing scans from acquired scans, catering to longitudinal infant studies.


Deep Uncalibrated Photometric Stereo via Inter-Intra Image Feature Fusion

no code implementations6 Aug 2022 Fangzhou Gao, Meng Wang, Lianghao Zhang, Li Wang, Jiawan Zhang

This paper presents a new method for deep uncalibrated photometric stereo, which efficiently utilizes the inter-image representation to guide the normal estimation.

Inverse Rendering

Convolutional Embedding Makes Hierarchical Vision Transformer Stronger

no code implementations27 Jul 2022 Cong Wang, Hongmin Xu, Xiong Zhang, Li Wang, Zhitong Zheng, Haifeng Liu

Vision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias.

Inductive Bias

Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection

1 code implementation10 Jul 2022 Lei Yang, Xinyu Zhang, Li Wang, Minghan Zhu, Chuang Zhang, Jun Li

Besides, by leveraging full training set and the additional 48K raw images of KITTI, it can further improve the MonoFlex by +4. 65% improvement on AP@0. 7 for car detection, reaching 18. 54% AP@0. 7, which ranks the 1st place among all monocular based methods on KITTI test leaderboard.

Autonomous Driving Model Optimization +2

Detecting fake news by enhanced text representation with multi-EDU-structure awareness

no code implementations30 May 2022 Yuhang Wang, Li Wang, Yanjie Yang, Yilin Zhang

Finally, the two EDU representations are incorporated as the enhanced text representation for fake news detection, using a gated recursive unit combined with a global attention mechanism.

Fake News Detection Graph Attention

Transfer Learning-based Channel Estimation in Orthogonal Frequency Division Multiplexing Systems Using Data-nulling Superimposed Pilots

1 code implementation28 May 2022 Chaojin Qing, Lei Dong, Li Wang, Guowei Ling, Jiafan Wang

To this end, a novel CE network for the DNSP scheme in OFDM systems is structured, which improves its estimation accuracy and alleviates the model mismatch.

Transfer Learning

Representing Brain Anatomical Regularity and Variability by Few-Shot Embedding

no code implementations26 May 2022 Lu Zhang, Xiaowei Yu, Yanjun Lyu, Zhengwang Wu, Haixing Dai, Lin Zhao, Li Wang, Gang Li, Tianming Liu, Dajiang Zhu

Our experimental results show that: 1) the learned embedding vectors can quantitatively encode the commonality and individuality of cortical folding patterns; 2) with the embeddings we can robustly infer the complicated many-to-many anatomical correspondences among different brains and 3) our model can be successfully transferred to new populations with very limited training samples.

Few-Shot Learning

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

ImpDet: Exploring Implicit Fields for 3D Object Detection

no code implementations31 Mar 2022 Xuelin Qian, Li Wang, Yi Zhu, Li Zhang, Yanwei Fu, xiangyang xue

Conventional 3D object detection approaches concentrate on bounding boxes representation learning with several parameters, i. e., localization, dimension, and orientation.

3D Object Detection object-detection +1

Learning Decoupling Features Through Orthogonality Regularization

no code implementations31 Mar 2022 Li Wang, Rongzhi Gu, Weiji Zhuang, Peng Gao, Yujun Wang, Yuexian Zou

Bearing this in mind, a two-branch deep network (KWS branch and SV branch) with the same network structure is developed and a novel decoupling feature learning method is proposed to push up the performance of KWS and SV simultaneously where speaker-invariant keyword representations and keyword-invariant speaker representations are expected respectively.

Keyword Spotting Speaker Verification

Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping

no code implementations8 Mar 2022 Yunxiang Li, Ruilong Dan, Shuai Wang, Yifan Cao, Xiangde Luo, Chenghao Tan, Gangyong Jia, Huiyu Zhou, You Zhang, Yaqi Wang, Li Wang

For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters.

Skull Stripping Source-Free Domain Adaptation

Computer-Aided Road Inspection: Systems and Algorithms

1 code implementation4 Mar 2022 Rui Fan, Sicen Guo, Li Wang, Mohammud Junaid Bocus

Road damage is an inconvenience and a safety hazard, severely affecting vehicle condition, driving comfort, and traffic safety.

Road Damage Detection

Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era

no code implementations22 Feb 2022 Changjiang Li, Li Wang, Shouling Ji, Xuhong Zhang, Zhaohan Xi, Shanqing Guo, Ting Wang

Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendors.

DeepFake Detection Face Swapping

A Framework for Multi-stage Bonus Allocation in meal delivery Platform

no code implementations22 Feb 2022 Zhuolin Wu, Li Wang, Fangsheng Huang, Linjun Zhou, Yu Song, Chengpeng Ye, Pengyu Nie, Hao Ren, Jinghua Hao, Renqing He, Zhizhao Sun

The semi-black-box acceptance probability model is employed to forecast the relationship between the bonus allocated to order and its acceptance probability, the Lagrangian dual-based dynamic programming algorithm aims to calculate the empirical Lagrangian multiplier for each allocation stage offline based on the historical data set, and the online allocation algorithm uses the results attained in the offline part to calculate a proper delivery bonus for each order.

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation

no code implementations NeurIPS 2021 Jamie Cui, Chaochao Chen, Lingjuan Lyu, Carl Yang, Li Wang

As a result, our model can not only improve the recommendation performance of the rating platform by incorporating the sparse social data on the social platform, but also protect data privacy of both platforms.

Information Retrieval Retrieval

Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation

no code implementations10 Feb 2022 Chaochao Chen, Huiwen Wu, Jiajie Su, Lingjuan Lyu, Xiaolin Zheng, Li Wang

To this end, PriCDR can not only protect the data privacy of the source domain, but also alleviate the data sparsity of the source domain.

Privacy Preserving Recommendation Systems +1

Higher Order Correlation Analysis for Multi-View Learning

no code implementations28 Jan 2022 Jiawang Nie, Li Wang, Zequn Zheng

This can be formulated as a low rank approximation problem with the higher order correlation tensor of multi-view data.


Backdoor Defense with Machine Unlearning

no code implementations24 Jan 2022 Yang Liu, Mingyuan Fan, Cen Chen, Ximeng Liu, Zhuo Ma, Li Wang, Jianfeng Ma

First, trigger pattern recovery is conducted to extract the trigger patterns infected by the victim model.

backdoor defense

The Implicit Regularization of Momentum Gradient Descent with Early Stopping

no code implementations14 Jan 2022 Li Wang, Yingcong Zhou, Zhiguo Fu

In the present paper, we characterize the implicit regularization of momentum gradient descent (MGD) with early stopping by comparing with the explicit $\ell_2$-regularization (ridge).


Deep neural networks for solving forward and inverse problems of (2+1)-dimensional nonlinear wave equations with rational solitons

no code implementations28 Dec 2021 Zijian Zhou, Li Wang, Zhenya Yan

In this paper, we investigate the forward problems on the data-driven rational solitons for the (2+1)-dimensional KP-I equation and spin-nonlinear Schr\"odinger (spin-NLS) equation via the deep neural networks leaning.

Data-driven discoveries of Bäcklund transforms and soliton evolution equations via deep neural network learning schemes

no code implementations18 Nov 2021 Zijian Zhou, Li Wang, Weifang Weng, Zhenya Yan

We introduce a deep neural network learning scheme to learn the B\"acklund transforms (BTs) of soliton evolution equations and an enhanced deep learning scheme for data-driven soliton equation discovery based on the known BTs, respectively.

Mathematical Models for Local Sensing Hashes

no code implementations16 Nov 2021 Li Wang, Lilon Wangner

As data volumes continue to grow, searches in data are becoming increasingly time-consuming.

Clustering Outlier Detection

Dispensed Transformer Network for Unsupervised Domain Adaptation

no code implementations28 Oct 2021 Yunxiang Li, Jingxiong Li, Ruilong Dan, Shuai Wang, Kai Jin, Guodong Zeng, Jun Wang, Xiangji Pan, Qianni Zhang, Huiyu Zhou, Qun Jin, Li Wang, Yaqi Wang

To mitigate this problem, a novel unsupervised domain adaptation (UDA) method named dispensed Transformer network (DTNet) is introduced in this paper.

Unsupervised Domain Adaptation

Enhanced ELM Based Channel Estimation for RIS-Assisted OFDM systems with Insufficient CP and Imperfect Hardware

no code implementations26 Oct 2021 Chaojin Qing, Li Wang, Lei Dong, Jiafan Wang

Reconfigurable intelligent surface (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems have aroused extensive research interests due to the controllable communication environment and the performance of combating multi-path interference.

Joint Model and Data Driven Receiver Design for Data-Dependent Superimposed Training Scheme with Imperfect Hardware

no code implementations26 Oct 2021 Chaojin Qing, Lei Dong, Li Wang, Jiafan Wang, Chuan Huang

Data-dependent superimposed training (DDST) scheme has shown the potential to achieve high bandwidth efficiency, while encounters symbol misidentification caused by hardware imperfection.

Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASR

no code implementations9 Oct 2021 Han Zhu, Li Wang, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan

In this work, in order to build a better pre-trained model for low-resource ASR, we propose a pre-training approach called wav2vec-S, where we use task-specific semi-supervised pre-training to refine the self-supervised pre-trained model for the ASR task thus more effectively utilize the capacity of the pre-trained model to generate task-specific representations for ASR.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans

no code implementations24 Sep 2021 Tai-Hsien Wu, Chunfeng Lian, Sanghee Lee, Matthew Pastewait, Christian Piers, Jie Liu, Fang Wang, Li Wang, Chiung-Ying Chiu, Wenchi Wang, Christina Jackson, Wei-Lun Chao, Dinggang Shen, Ching-Chang Ko

Our TS-MDL first adopts an end-to-end \emph{i}MeshSegNet method (i. e., a variant of the existing MeshSegNet with both improved accuracy and efficiency) to label each tooth on the downsampled scan.

Code Generation

Structure-Enhanced Pop Music Generation via Harmony-Aware Learning

1 code implementation14 Sep 2021 Xueyao Zhang, Jinchao Zhang, Yao Qiu, Li Wang, Jie zhou

Experimental results reveal that compared to the existing methods, HAT owns a much better understanding of the structure and it can also improve the quality of generated music, especially in the form and texture.

Music Generation

Text Anchor Based Metric Learning for Small-footprint Keyword Spotting

no code implementations12 Aug 2021 Li Wang, Rongzhi Gu, Nuo Chen, Yuexian Zou

Recently proposed metric learning approaches improved the generalizability of models for the KWS task, and 1D-CNN based KWS models have achieved the state-of-the-arts (SOTA) in terms of model size.

Metric Learning Small-Footprint Keyword Spotting

Privacy Threats Analysis to Secure Federated Learning

no code implementations24 Jun 2021 Yuchen Li, Yifan Bao, Liyao Xiang, Junhan Liu, Cen Chen, Li Wang, Xinbing Wang

Federated learning is emerging as a machine learning technique that trains a model across multiple decentralized parties.

BIG-bench Machine Learning Federated Learning +1

Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis

no code implementations22 Jun 2021 Miao Zhang, Wei Huang, Li Wang

We investigate this question through the lens of edge connectivity, and provide an affirmative answer by defining a connectivity concept, ZERo-cost Operation Sensitivity (ZEROS), to score the importance of candidate operations in DARTS at initialization.

Network Pruning Neural Architecture Search

Representative Functional Connectivity Learning for Multiple Clinical groups in Alzheimer's Disease

no code implementations14 Jun 2021 Lu Zhang, Xiaowei Yu, Yanjun Lyu, Li Wang, Dajiang Zhu

By mapping the learned clinical group related feature vectors to the original FC space, representative FCs were constructed for each group.

Multi-class Classification

AGSFCOS: Based on attention mechanism and Scale-Equalizing pyramid network of object detection

no code implementations20 May 2021 Li Wang, Wei Xiang, Ruhui Xue, Kaida Zou, Laili Zhu

In order to solve the above problems, Experiments show that our model has a certain improvement in accuracy compared with the current popular detection models on the COCO dataset, the designed attention mechanism module can capture contextual information well, improve detection accuracy, and use sepc network to help balance abstract and detailed information, and reduce the problem of semantic gap in the feature pyramid network.

object-detection Object Detection

Towards a Model for LSH

no code implementations11 May 2021 Li Wang

Instead, approximated index structures offer a good opportunity to significantly accelerate the neighbor search for clustering and outlier detection and to have the lowest possible error rate in the results of the algorithms.

Clustering Outlier Detection

Lite-FPN for Keypoint-based Monocular 3D Object Detection

1 code implementation1 May 2021 Lei Yang, Xinyu Zhang, Li Wang, Minghan Zhu, Jun Li

3D object detection with a single image is an essential and challenging task for autonomous driving.

Autonomous Driving Monocular 3D Object Detection +1

Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving

no code implementations21 Mar 2021 Li Wang, Dong Li, Han Liu, Jinzhang Peng, Lu Tian, Yi Shan

Our goal is to train a unified model for improving the performance in each dataset by leveraging information from all the datasets.

3D Semantic Segmentation Autonomous Driving +3

An Efficient Autocalibration Method for Triaxial Gyroscope without External Device

no code implementations20 Mar 2021 Li Wang, Steven Su

We empirically validate the effectiveness of the proposed method on two commonly used low-cost gyroscope and achieve real-time calibration on a low-energy microcontroller.

Experimental Design

S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

2 code implementations15 Mar 2021 Li Wang, Chenfei Wang, Xinyu Zhang, Tianwei Lan, Jun Li

3D object detection plays a crucial role in environmental perception for autonomous vehicles, which is the prerequisite of decision and control.

3D Object Detection Autonomous Vehicles +1

DM algorithms in healthindustry

no code implementations2 Mar 2021 Li Wang

Modern multi-core processors consist of several (2 to over 100) computer cores, which work independently of each other according to the principle of "multiple instruction multiple data" (MIMD).

EEG Electroencephalogram (EEG)

Disease2Vec: Representing Alzheimer's Progression via Disease Embedding Tree

no code implementations13 Feb 2021 Lu Zhang, Li Wang, Tianming Liu, Dajiang Zhu

By disease em-bedding, the framework generates a disease embedding tree (DETree) which effectively represents different clinical stages as a tree trajectory reflecting AD progression and thus can be used to predict clinical status by projecting individuals onto this continuous trajectory.

Multi-class Classification

Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and Cognitive Radio

no code implementations27 Jan 2021 Xin Liu, Kwok-Yan Lam, Feng Li, Jun Zhao, Li Wang

ISTCN aims to provide high speed and pervasive network services by integrating broadband terrestrial mobile networks with satellite communication networks.


Data-driven peakon and periodic peakon travelling wave solutions of some nonlinear dispersive equations via deep learning

no code implementations12 Jan 2021 Li Wang, Zhenya Yan

In the field of mathematical physics, there exist many physically interesting nonlinear dispersive equations with peakon solutions, which are solitary waves with discontinuous first-order derivative at the wave peak.

Experimental Design

Trace Ratio Optimization with an Application to Multi-view Learning

no code implementations12 Jan 2021 Li Wang, Lei-Hong Zhang, Ren-cang Li

A trace ratio optimization problem over the Stiefel manifold is investigated from the perspectives of both theory and numerical computations.


Data-driven rogue waves and parameter discovery in the defocusing NLS equation with a potential using the PINN deep learning

no code implementations18 Dec 2020 Li Wang, Zhenya Yan

Moreover, the multi-layer PINN algorithm can also be used to learn the parameter in the defocusing NLS equation with the time-dependent potential under the sense of the rogue wave solution.

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design

no code implementations17 Dec 2020 Jun Zhou, Longfei Zheng, Chaochao Chen, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin

In this paper, we propose SPNN - a Scalable and Privacy-preserving deep Neural Network learning framework, from algorithmic-cryptographic co-perspective.

Privacy Preserving

Complex Relation Extraction: Challenges and Opportunities

no code implementations9 Dec 2020 Haiyun Jiang, Qiaoben Bao, Qiao Cheng, Deqing Yang, Li Wang, Yanghua Xiao

In recent years, many complex relation extraction tasks, i. e., the variants of simple binary relation extraction, are proposed to meet the complex applications in practice.

Binary Relation Extraction

Computer Stereo Vision for Autonomous Driving

no code implementations6 Dec 2020 Rui Fan, Li Wang, Mohammud Junaid Bocus, Ioannis Pitas

As an important component of autonomous systems, autonomous car perception has had a big leap with recent advances in parallel computing architectures.

Autonomous Driving Image Segmentation +3

Uncorrelated Semi-paired Subspace Learning

no code implementations22 Nov 2020 Li Wang, Lei-Hong Zhang, Chungen Shen, Ren-cang Li

However, unpaired data can be more abundant in reality than paired ones and simply ignoring all unpaired data incur tremendous waste in resources.


Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications

no code implementations20 Nov 2020 Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, Li Wang

In this paper, to fill this gap, we summarize the open problems for privacy preserving KG in data isolation setting and propose possible solutions for them.

Privacy Preserving

A Theoretical Perspective on Differentially Private Federated Multi-task Learning

no code implementations14 Nov 2020 Huiwen Wu, Cen Chen, Li Wang

In the era of big data, the need to expand the amount of data through data sharing to improve model performance has become increasingly compelling.

Multi-Task Learning

ASFGNN: Automated Separated-Federated Graph Neural Network

no code implementations6 Nov 2020 Longfei Zheng, Jun Zhou, Chaochao Chen, Bingzhe Wu, Li Wang, Benyu Zhang

Specifically, to solve the data Non-IID problem, we first propose a separated-federated GNN learning model, which decouples the training of GNN into two parts: the message passing part that is done by clients separately, and the loss computing part that is learnt by clients federally.

Bayesian Optimization

Domain Adaptation Using Class Similarity for Robust Speech Recognition

1 code implementation5 Nov 2020 Han Zhu, Jiangjiang Zhao, Yuling Ren, Li Wang, Pengyuan Zhang

Then, for each class, probabilities of this class are used to compute a mean vector, which we refer to as mean soft labels.

Domain Adaptation Robust Speech Recognition +1

Multi-Accent Adaptation based on Gate Mechanism

no code implementations5 Nov 2020 Han Zhu, Li Wang, Pengyuan Zhang, Yonghong Yan

To jointly train the acoustic model and the accent classifier, we propose the multi-task learning with gate mechanism (MTL-G).

Multi-Task Learning speech-recognition +1

What About Inputing Policy in Value Function: Policy Representation and Policy-extended Value Function Approximator

no code implementations NeurIPS 2021 Hongyao Tang, Zhaopeng Meng, Jianye Hao, Chen Chen, Daniel Graves, Dong Li, Changmin Yu, Hangyu Mao, Wulong Liu, Yaodong Yang, Wenyuan Tao, Li Wang

We study Policy-extended Value Function Approximator (PeVFA) in Reinforcement Learning (RL), which extends conventional value function approximator (VFA) to take as input not only the state (and action) but also an explicit policy representation.

Continuous Control Contrastive Learning +3

Orthogonal Multi-view Analysis by Successive Approximations via Eigenvectors

no code implementations4 Oct 2020 Li Wang, Leihong Zhang, Chungen Shen, Ren-cang Li

We propose a unified framework for multi-view subspace learning to learn individual orthogonal projections for all views.

General Classification Multi-Label Classification

Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy

no code implementations24 Sep 2020 Bin Zhang, Cen Chen, Li Wang

The success of machine learning algorithms often relies on a large amount of high-quality data to train well-performed models.

Federated Learning Privacy Preserving +1

A Comprehensive Analysis of Information Leakage in Deep Transfer Learning

no code implementations4 Sep 2020 Cen Chen, Bingzhe Wu, Minghui Qiu, Li Wang, Jun Zhou

To the best of our knowledge, our study is the first to provide a thorough analysis of the information leakage issues in deep transfer learning methods and provide potential solutions to the issue.

Transfer Learning

When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control

no code implementations20 Aug 2020 Chaochao Chen, Jun Zhou, Li Wang, Xibin Wu, Wenjing Fang, Jin Tan, Lei Wang, Alex X. Liu, Hao Wang, Cheng Hong

In this paper, we first present CAESAR, which combines HE and SS to build secure large-scale sparse logistic regression model and achieves both efficiency and security.


Multi-view Orthonormalized Partial Least Squares: Regularizations and Deep Extensions

no code implementations9 Jul 2020 Li Wang, Ren-cang Li, Wen-Wei

Building on the least squares reformulation of OPLS, we propose a unified multi-view learning framework to learn a classifier over a common latent space shared by all views.

Cross-Modal Retrieval MULTI-VIEW LEARNING +1

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

no code implementations4 Jul 2020 Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying WEI, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang

Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners.

Brain Segmentation

Dual Super-Resolution Learning for Semantic Segmentation

1 code implementation CVPR 2020 Li Wang, Dong Li, Yousong Zhu, Lu Tian, Yi Shan

Specifically, for semantic segmentation on CityScapes, we can achieve \geq2% higher mIoU with similar FLOPs, and keep the performance with 70% FLOPs.

Image Super-Resolution Pose Estimation +2

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

no code implementations25 May 2020 Chaochao Chen, Jun Zhou, Longfei Zheng, Huiwen Wu, Lingjuan Lyu, Jia Wu, Bingzhe Wu, Ziqi Liu, Li Wang, Xiaolin Zheng

Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between different nodes.

Classification General Classification +2

Deep Tensor CCA for Multi-view Learning

1 code implementation25 May 2020 Hok Shing Wong, Li Wang, Raymond Chan, Tieyong Zeng

We present Deep Tensor Canonical Correlation Analysis (DTCCA), a method to learn complex nonlinear transformations of multiple views (more than two) of data such that the resulting representations are linearly correlated in high order.

MULTI-VIEW LEARNING Tensor Decomposition

Large-Scale Secure XGB for Vertical Federated Learning

no code implementations18 May 2020 Wenjing Fang, Derun Zhao, Jin Tan, Chaochao Chen, Chaofan Yu, Li Wang, Lei Wang, Jun Zhou, Benyu Zhang

Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of privacy regulations come into force.

BIG-bench Machine Learning Federated Learning +1

Secret Sharing based Secure Regressions with Applications

no code implementations10 Apr 2020 Chaochao Chen, Liang Li, Wenjing Fang, Jun Zhou, Li Wang, Lei Wang, Shuang Yang, Alex Liu, Hao Wang

Nowadays, the utilization of the ever expanding amount of data has made a huge impact on web technologies while also causing various types of security concerns.


Industrial Scale Privacy Preserving Deep Neural Network

no code implementations11 Mar 2020 Longfei Zheng, Chaochao Chen, Yingting Liu, Bingzhe Wu, Xibin Wu, Li Wang, Lei Wang, Jun Zhou, Shuang Yang

Deep Neural Network (DNN) has been showing great potential in kinds of real-world applications such as fraud detection and distress prediction.

Fraud Detection Privacy Preserving

Practical Privacy Preserving POI Recommendation

no code implementations5 Mar 2020 Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjin Fang, Li Wang, Yuan Qi, Xiaolin Zheng

Meanwhile, the public data need to be accessed by all the users are kept by the recommender to reduce the storage costs of users' devices.

Federated Learning Privacy Preserving

Secure Social Recommendation based on Secret Sharing

no code implementations6 Feb 2020 Chaochao Chen, Liang Li, Bingzhe Wu, Cheng Hong, Li Wang, Jun Zhou

It is well known that social information, which is rich on social platforms such as Facebook, are useful to recommender systems.

Privacy Preserving Recommendation Systems

Privacy Preserving PCA for Multiparty Modeling

no code implementations6 Feb 2020 Yingting Liu, Chaochao Chen, Longfei Zheng, Li Wang, Jun Zhou, Guiquan Liu, Shuang Yang

In this paper, we present a general multiparty modeling paradigm with Privacy Preserving Principal Component Analysis (PPPCA) for horizontally partitioned data.

Fraud Detection Privacy Preserving

Large-Scale Semi-Supervised Learning via Graph Structure Learning over High-Dense Points

no code implementations4 Dec 2019 Zitong Wang, Li Wang, Raymond Chan, Tieyong Zeng

A novel approach is then proposed to construct the graph of the input data from the learned graph of a small number of vertexes with some preferred properties.

Graph structure learning

There is Limited Correlation between Coverage and Robustness for Deep Neural Networks

no code implementations14 Nov 2019 Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jin Song Dong, Dai Ting

In this work, we conduct an empirical study to evaluate the relationship between coverage, robustness and attack/defense metrics for DNN.

Face Recognition Malware Detection

Hetero-Center Loss for Cross-Modality Person Re-Identification

no code implementations22 Oct 2019 Yuanxin Zhu, Zhao Yang, Li Wang, Sai Zhao, Xiao Hu, Dapeng Tao

With the joint supervision of Cross-Entropy (CE) loss and HC loss, the network is trained to achieve two vital objectives, inter-class discrepancy and intra-class cross-modality similarity as much as possible.

Cross-Modality Person Re-identification Person Re-Identification

Unsupervised Multi-stream Highlight detection for the Game "Honor of Kings"

no code implementations14 Oct 2019 Li Wang, Zixun Sun, Wentao Yao, Hui Zhan, Chengwei Zhu

With the increasing popularity of E-sport live, Highlight Flashback has been a critical functionality of live platforms, which aggregates the overall exciting fighting scenes in a few seconds.

Highlight Detection Test

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics

no code implementations5 Oct 2019 Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan YAO, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou

Based on this framework, we demonstrate that SGLD can prevent the information leakage of the training dataset to a certain extent.

Generalization Bounds

A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis

no code implementations25 Sep 2019 Leihong Zhang, Li Wang, Zhaojun Bai, Ren-cang Li

In this paper, we propose an alternating numerical scheme whose core is the sub-maximization problem in the trace-fractional form with an orthogonal constraint.

Multi-Label Classification

Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection

no code implementations NeurIPS 2019 Bingzhe Wu, Shiwan Zhao, Chaochao Chen, Haoyang Xu, Li Wang, Xiaolu Zhang, Guangyu Sun, Jun Zhou

In this paper, we aim to understand the generalization properties of generative adversarial networks (GANs) from a new perspective of privacy protection.

Probabilistic Structure Learning for EEG/MEG Source Imaging with Hierarchical Graph Prior

no code implementations5 Jun 2019 Feng Liu, Li Wang, Yifei Lou, Ren-cang Li, Patrick Purdon

Traditional EEG/MEG Source Imaging (ESI) methods usually assume that either source activity at different time points is unrelated, or that similar spatiotemporal patterns exist across an entire study period.

EEG Electroencephalogram (EEG)

Glioma Grade Prediction Using Wavelet Scattering-Based Radiomics

no code implementations23 May 2019 Qijian Chen, Lihui Wang, Li Wang, Zeyu Deng, Jian Zhang, Yuemin Zhu

Glioma grading before surgery is very critical for the prognosis prediction and treatment plan making.

Dimensionality Reduction regression

Convolutional Restricted Boltzmann Machine Based-Radiomics for Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer

no code implementations23 May 2019 Li Wang, Lihui Wang, Qijian Chen, Caixia Sun, Xinyu Cheng, Yue-Min Zhu

We proposed a novel convolutional restricted Boltzmann machine CRBM-based radiomic method for predicting pathologic complete response (pCR) to neoadjuvant chemotherapy treatment (NACT) in breast cancer.

feature selection

From Abstractions to "Natural Languages" for Coordinating Planning Agents

no code implementations1 May 2019 Yu Zhang, Li Wang

We formulate this language construction problem and show that it is NEXP-complete.

Multi-Agent Path Finding

Fusion-supervised Deep Cross-modal Hashing

no code implementations25 Apr 2019 Li Wang, Lei Zhu, En Yu, Jiande Sun, Huaxiang Zhang

Deep hashing has recently received attention in cross-modal retrieval for its impressive advantages.

Cross-Modal Retrieval Deep Hashing

A Comparison Study of Credit Card Fraud Detection: Supervised versus Unsupervised

no code implementations24 Apr 2019 Xuetong Niu, Li Wang, Xulei Yang

In this study, we perform a comparison study of credit card fraud detection by using various supervised and unsupervised approaches.

Fraud Detection Unsupervised Anomaly Detection

Learning Actor Relation Graphs for Group Activity Recognition

2 code implementations CVPR 2019 Jianchao Wu, Li-Min Wang, Li Wang, Jie Guo, Gangshan Wu

To this end, we propose to build a flexible and efficient Actor Relation Graph (ARG) to simultaneously capture the appearance and position relation between actors.

Action Recognition Group Activity Recognition

Facial Feature Embedded CycleGAN for VIS-NIR Translation

no code implementations20 Apr 2019 Huijiao Wang, Li Wang, Xulei Yang, Lei Yu, Haijian Zhang

VIS-NIR face recognition remains a challenging task due to the distinction between spectral components of two modalities and insufficient paired training data.

Face Recognition Translation

Spherical U-Net on Cortical Surfaces: Methods and Applications

no code implementations1 Apr 2019 Fenqiang Zhao, Shunren Xia, Zhengwang Wu, Dingna Duan, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen, Gang Li

In this paper, by leveraging the regular and consistent geometric structure of the resampled cortical surface mapped onto the spherical space, we propose a novel convolution filter analogous to the standard convolution on the image grid.

CODA: Counting Objects via Scale-aware Adversarial Density Adaption

1 code implementation25 Mar 2019 Li Wang, Yongbo Li, xiangyang xue

Extensive experiments demonstrate that our network produces much better results on unseen datasets compared with existing counting adaption models.

Crowd Counting

Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses

no code implementations19 Mar 2019 Rong Jin, David Simchi-Levi, Li Wang, Xinshang Wang, Sen Yang

In this paper, we study algorithms for dynamically identifying a large number of products (i. e., SKUs) with top customer purchase probabilities on the fly, from an ocean of potential products to offer on retailers' ultra-fast delivery platforms.

Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction

no code implementations25 Sep 2018 Hongyao Tang, Jianye Hao, Tangjie Lv, Yingfeng Chen, Zongzhang Zhang, Hangtian Jia, Chunxu Ren, Yan Zheng, Zhaopeng Meng, Changjie Fan, Li Wang

Besides, we propose a new experience replay mechanism to alleviate the issue of the sparse transitions at the high level of abstraction and the non-stationarity of multiagent learning.

reinforcement-learning Reinforcement Learning (RL)

Crowd Counting with Density Adaption Networks

no code implementations26 Jun 2018 Li Wang, Weiyuan Shao, Yao Lu, Hao Ye, Jian Pu, Yingbin Zheng

Crowd counting is one of the core tasks in various surveillance applications.

Crowd Counting

A practical convolutional neural network as loop filter for intra frame

no code implementations16 May 2018 Xiaodan Song, Jiabao Yao, Lulu Zhou, Li Wang, Xiaoyang Wu, Di Xie, ShiLiang Pu

It aims to design a single CNN model with low redundancy to adapt to decoded frames with different qualities and ensure consistency.


An Optimal Rewiring Strategy for Reinforcement Social Learning in Cooperative Multiagent Systems

no code implementations13 May 2018 Hongyao Tang, Li Wang, Zan Wang, Tim Baarslag, Jianye Hao

Multiagent coordination in cooperative multiagent systems (MASs) has been widely studied in both fixed-agent repeated interaction setting and the static social learning framework.

A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization

no code implementations9 May 2018 Li Wang, Junlin Yao, Yunzhe Tao, Li Zhong, Wei Liu, Qiang Du

In this paper, we propose a deep learning approach to tackle the automatic summarization tasks by incorporating topic information into the convolutional sequence-to-sequence (ConvS2S) model and using self-critical sequence training (SCST) for optimization.

Abstractive Text Summarization Informativeness

Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity

no code implementations28 Apr 2018 Xiaohuan Cao, Jianhua Yang, Li Wang, Zhong Xue, Qian Wang, Dinggang Shen

In this paper, we propose to train a non-rigid inter-modality image registration network, which can directly predict the transformation field from the input multimodal images, such as CT and MR images.

Image Registration

Medical Image Synthesis with Deep Convolutional Adversarial Networks

1 code implementation IEEE Transactions on Biomedical Engineering 2018 Dong Nie, Roger Trullo, Jun Lian, Li Wang, Caroline Petitjean, Su Ruan, Qian Wang, and Dinggang Shen, Fellow, IEEE

To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN.

Image Generation

Time-sensitive Customer Churn Prediction based on PU Learning

no code implementations27 Feb 2018 Li Wang, Chaochao Chen, Jun Zhou, Xiaolong Li

With the fast development of Internet companies throughout the world, customer churn has become a serious concern.

TextZoo, a New Benchmark for Reconsidering Text Classification

no code implementations10 Feb 2018 Benyou Wang, Li Wang, Qikang Wei, Lichun Liu

Text representation is a fundamental concern in Natural Language Processing, especially in text classification.

General Classification text-classification +1

Barrier-Certified Adaptive Reinforcement Learning with Applications to Brushbot Navigation

no code implementations29 Jan 2018 Motoya Ohnishi, Li Wang, Gennaro Notomista, Magnus Egerstedt

This paper presents a safe learning framework that employs an adaptive model learning algorithm together with barrier certificates for systems with possibly nonstationary agent dynamics.

reinforcement-learning Reinforcement Learning (RL)

Learning Hierarchical Features for Visual Object Tracking with Recursive Neural Networks

no code implementations6 Jan 2018 Li Wang, Ting Liu, Bing Wang, Xulei Yang, Gang Wang

First, we learn RNN parameters to discriminate between the target object and background in the first frame of a test sequence.

Test Visual Object Tracking

Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation

1 code implementation14 Dec 2017 Jose Dolz, Christian Desrosiers, Li Wang, Jing Yuan, Dinggang Shen, Ismail Ben Ayed

We report evaluations of our method on the public data of the MICCAI iSEG-2017 Challenge on 6-month infant brain MRI segmentation, and show very competitive results among 21 teams, ranking first or second in most metrics.

Image Segmentation Infant Brain Mri Segmentation +3

Safe Learning of Quadrotor Dynamics Using Barrier Certificates

no code implementations16 Oct 2017 Li Wang, Evangelos A. Theodorou, Magnus Egerstedt

The barrier certificates establish a non-conservative forward invariant safe region, in which high probability safety guarantees are provided based on the statistics of the Gaussian Process.

Gaussian Processes

Arbitrary-Oriented Scene Text Detection via Rotation Proposals

4 code implementations3 Mar 2017 Jianqi Ma, Weiyuan Shao, Hao Ye, Li Wang, Hong Wang, Yingbin Zheng, xiangyang xue

This paper introduces a novel rotation-based framework for arbitrary-oriented text detection in natural scene images.

Region Proposal Scene Text Detection +1

Cross-model convolutional neural network for multiple modality data representation

no code implementations19 Nov 2016 Yanbin Wu, Li Wang, Fan Cui, Hongbin Zhai, Baoming Dong, Jim Jing-Yan Wang

A novel data representation method of convolutional neural net- work (CNN) is proposed in this paper to represent data of different modalities.

Probabilistic Dimensionality Reduction via Structure Learning

no code implementations16 Oct 2016 Li Wang

Based on this framework, we present a new model, which is able to learn a smooth skeleton of embedding points in a low-dimensional space from high-dimensional noisy data.

Clustering Data Visualization +1

Joint Learning of Siamese CNNs and Temporally Constrained Metrics for Tracklet Association

no code implementations15 May 2016 Bing Wang, Li Wang, Bing Shuai, Zhen Zuo, Ting Liu, Kap Luk Chan, Gang Wang

Then the Siamese CNN and temporally constrained metrics are jointly learned online to construct the appearance-based tracklet affinity models.

Multi-Object Tracking Multi-Task Learning

Shape Animation with Combined Captured and Simulated Dynamics

no code implementations6 Jan 2016 Benjamin Allain, Li Wang, Jean-Sebastien Franco, Franck Hetroy, Edmond Boyer

Instead of using the dominant surface-based geometric representation of the capture, which is less suitable for volumetric effects, our pipeline exploits Centroidal Voronoi tessellation decompositions as unified volumetric representation of the real captured actor, which we show can be used seamlessly as a building block for all processing stages, from capture and tracking to virtual physic simulation.

Recent Advances in Convolutional Neural Networks

no code implementations22 Dec 2015 Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Li Wang, Gang Wang, Jianfei Cai, Tsuhan Chen

In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing.

speech-recognition Speech Recognition

Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey

no code implementations10 Dec 2015 Li Wang, Dennis Sng

Deep learning has recently achieved very promising results in a wide range of areas such as computer vision, speech recognition and natural language processing.

Face Recognition General Classification +7

A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation

no code implementations9 Dec 2015 Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun

As showcases, models that can learn a spanning tree or a weighted undirected $\ell_1$ graph are proposed, and a new learning algorithm is developed that learns a set of principal points and a graph structure from data, simultaneously.

Graph Embedding Graph Learning

Video Tracking Using Learned Hierarchical Features

no code implementations25 Nov 2015 Li Wang, Ting Liu, Gang Wang, Kap Luk Chan, Qingxiong Yang

The adaptation is conducted in both layers of the deep feature learning module so as to include appearance information of the specific target object.

Domain Adaptation Network Embedding +1

Tracklet Association by Online Target-Specific Metric Learning and Coherent Dynamics Estimation

no code implementations20 Nov 2015 Bing Wang, Gang Wang, Kap Luk Chan, Li Wang

In this paper, we present a novel method based on online target-specific metric learning and coherent dynamics estimation for tracklet (track fragment) association by network flow optimization in long-term multi-person tracking.

Metric Learning

Tracklet Association with Online Target-Specific Metric Learning

no code implementations CVPR 2014 Bing Wang, Gang Wang, Kap Luk Chan, Li Wang

In our method, target-specific similarity metrics are learned, which give rise to the appearance-based models used in the tracklet affinity estimation.

Metric Learning

Modeling Based on Elman Wavelet Neural Network for Class-D Power Amplifiers

no code implementations12 Sep 2013 Li Wang, Jie Shao, Yaqin Zhong, Weisong Zhao, Reza Malekian

In Class-D Power Amplifiers (CDPAs), the power supply noise can intermodulate with the input signal, manifesting into power-supply induced intermodulation distortion (PS-IMD) and due to the memory effects of the system, there exist asymmetries in the PS-IMDs.

Matching Pursuit LASSO Part II: Applications and Sparse Recovery over Batch Signals

no code implementations20 Feb 2013 Mingkui Tan, Ivor W. Tsang, Li Wang

Matching Pursuit LASSIn Part I \cite{TanPMLPart1}, a Matching Pursuit LASSO ({MPL}) algorithm has been presented for solving large-scale sparse recovery (SR) problems.

Compressive Sensing Face Recognition

Towards Ultrahigh Dimensional Feature Selection for Big Data

no code implementations24 Sep 2012 Mingkui Tan, Ivor W. Tsang, Li Wang

In this paper, we present a new adaptive feature scaling scheme for ultrahigh-dimensional feature selection on Big Data.

feature selection Selection bias

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