Search Results for author: Xin Zhang

Found 107 papers, 22 papers with code

Sociolectal Analysis of Pretrained Language Models

no code implementations EMNLP 2021 Sheng Zhang, Xin Zhang, Weiming Zhang, Anders Søgaard

Using data from English cloze tests, in which subjects also self-reported their gender, age, education, and race, we examine performance differences of pretrained language models across demographic groups, defined by these (protected) attributes.

Distribution-restrained Softmax Loss for the Model Robustness

no code implementations22 Mar 2023 Hao Wang, Chen Li, JinZhe Jiang, Xin Zhang, YaQian Zhao, Weifeng Gong

Recently, the robustness of deep learning models has received widespread attention, and various methods for improving model robustness have been proposed, including adversarial training, model architecture modification, design of loss functions, certified defenses, and so on.

Machine Learning Automated Approach for Enormous Synchrotron X-Ray Diffraction Data Interpretation

no code implementations20 Mar 2023 Xiaodong Zhao, YiXuan Luo, Juejing Liu, Wenjun Liu, Kevin M. Rosso, Xiaofeng Guo, Tong Geng, Ang Li, Xin Zhang

This study highlighted the importance of labeled experimental patterns on the training of DNN models to solve u-XRD mapping data from in-situ experiments involving liquid phase.

Co-Occurrence Matters: Learning Action Relation for Temporal Action Localization

no code implementations15 Mar 2023 Congqi Cao, Yizhe WANG, Yue Lu, Xin Zhang, Yanning Zhang

Existing works in this field mainly suffer from two weaknesses: (1) They often neglect the multi-label case and only focus on temporal modeling.

Temporal Action Localization

PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities

no code implementations5 Mar 2023 Zhuqing Liu, Xin Zhang, Songtao Lu, Jia Liu

Decentralized min-max optimization problems with domain constraints underpins many important ML applications, including multi-agent ML fairness assurance, and policy evaluations in multi-agent reinforcement learning.

Fairness Multi-agent Reinforcement Learning

Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction

1 code implementation25 Feb 2023 Yu Liu, Xin Zhang, Jingtao Ding, Yanxin Xi, Yong Li

To address such issues, in this paper, we propose a Knowledge-infused Contrastive Learning (KnowCL) model for urban imagery-based socioeconomic prediction.

Contrastive Learning Representation Learning

sMRI-PatchNet: A novel explainable patch-based deep learning network for Alzheimer's disease diagnosis and discriminative atrophy localisation with Structural MRI

no code implementations17 Feb 2023 Xin Zhang, Liangxiu Han, Lianghao Han, Haoming Chen, Darren Dancey, Daoqiang Zhang

Specifically, it consists of two primary components: 1) A fast and efficient explainable patch selection mechanism for determining the most discriminative patches based on computing the SHapley Additive exPlanations (SHAP) contribution to a transfer learning model for AD diagnosis on massive medical data; and 2) A novel patch-based network for extracting deep features and AD classfication from the selected patches with position embeddings to retain position information, capable of capturing the global and local information of inter- and intra-patches.

Transfer Learning

Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection

1 code implementation23 Dec 2022 Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

To bridge the gap, we introduce a Personalized Subgraph Selector (PS2) as a plug-and-play framework to automatically, personally, and inductively identify optimal subgraphs for different edges when performing GNNLP.

Link Prediction

Weakly Supervised Video Anomaly Detection Based on Cross-Batch Clustering Guidance

no code implementations16 Dec 2022 Congqi Cao, Xin Zhang, Shizhou Zhang, Peng Wang, Yanning Zhang

To enhance the discriminative power of features, we propose a batch clustering based loss to encourage a clustering branch to generate distinct normal and abnormal clusters based on a batch of data.

Anomaly Detection Video Anomaly Detection

Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech

no code implementations4 Nov 2022 Xin Zhang, Iván Vallés-Pérez, Andreas Stolcke, Chengzhu Yu, Jasha Droppo, Olabanji Shonibare, Roberto Barra-Chicote, Venkatesh Ravichandran

By fine-tuning an ASR model on synthetic stuttered speech we are able to reduce word error by 5. 7% relative on stuttered utterances, with only minor (<0. 2% relative) degradation for fluent utterances.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Depth Monocular Estimation with Attention-based Encoder-Decoder Network from Single Image

no code implementations24 Oct 2022 Xin Zhang, Rabab Abdelfattah, Yuqi Song, Samuel A. Dauchert, XiaoFeng Wang

Depth information is the foundation of perception, essential for autonomous driving, robotics, and other source-constrained applications.

Autonomous Driving SSIM

An Effective Approach for Multi-label Classification with Missing Labels

no code implementations24 Oct 2022 Xin Zhang, Rabab Abdelfattah, Yuqi Song, XiaoFeng Wang

Through comprehensive experiments on three large-scale multi-label image datasets, i. e. MS-COCO, NUS-WIDE, and Pascal VOC12, we show that our method can handle the imbalance between positive labels and negative labels, while still outperforming existing missing-label learning approaches in most cases, and in some cases even approaches with fully labeled datasets.

Classification Multi-class Classification +2

Extending Phrase Grounding with Pronouns in Visual Dialogues

1 code implementation23 Oct 2022 Panzhong Lu, Xin Zhang, Meishan Zhang, Min Zhang

First, we construct a dataset of phrase grounding with both noun phrases and pronouns to image regions.

Phrase Grounding

G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification

no code implementations20 Oct 2022 Rabab Abdelfattah, Xin Zhang, Mostafa M. Fouda, XiaoFeng Wang, Song Wang

To effectively address partial-label classification, this paper proposes an end-to-end Generic Game-theoretic Network (G2NetPL) for partial-label learning, which can be applied to most partial-label settings, including a very challenging, but annotation-efficient case where only a subset of the training images are labeled, each with only one positive label, while the rest of the training images remain unlabeled.

Multi-Label Classification Multi-Label Image Classification +2

SAGDA: Achieving $\mathcal{O}(ε^{-2})$ Communication Complexity in Federated Min-Max Learning

no code implementations2 Oct 2022 Haibo Yang, Zhuqing Liu, Xin Zhang, Jia Liu

To lower the communication complexity of federated min-max learning, a natural approach is to utilize the idea of infrequent communications (through multiple local updates) same as in conventional federated learning.

Federated Learning

Passive Non-line-of-sight Imaging for Moving Targets with an Event Camera

no code implementations27 Sep 2022 Conghe Wang, Yutong He, Xia Wang, Honghao Huang, Changda Yan, Xin Zhang, Hongwei Chen

Non-line-of-sight (NLOS) imaging is an emerging technique for detecting objects behind obstacles or around corners.

Graph Contrastive Learning with Personalized Augmentation

no code implementations14 Sep 2022 Xin Zhang, Qiaoyu Tan, Xiao Huang, Bo Li

Thus, blindly augmenting all graphs without considering their individual characteristics may undermine the performance of GCL arts. To deal with this, we propose the first principled framework, termed as \textit{G}raph contrastive learning with \textit{P}ersonalized \textit{A}ugmentation (GPA), to advance conventional GCL by allowing each graph to choose its own suitable augmentation operations. In essence, GPA infers tailored augmentation strategies for each graph based on its topology and node attributes via a learnable augmentation selector, which is a plug-and-play module and can be effectively trained with downstream GCL models end-to-end.

Contrastive Learning Data Augmentation

ReX: A Framework for Generating Local Explanations to Recurrent Neural Networks

no code implementations8 Sep 2022 Junhao Liu, Xin Zhang

We propose a general framework to adapt various local explanation techniques to recurrent neural networks.

Anomaly Detection Sentiment Analysis

A PDE approach for regret bounds under partial monitoring

no code implementations2 Sep 2022 Erhan Bayraktar, Ibrahim Ekren, Xin Zhang

In this paper, we study a learning problem in which a forecaster only observes partial information.

Swin-transformer-yolov5 For Real-time Wine Grape Bunch Detection

no code implementations30 Aug 2022 Shenglian Lu, Xiaoyu Liu, Zixaun He, Manoj Karkee, Xin Zhang

Results showed that the proposed Swin-T-YOLOv5 outperformed all other studied models for grape bunch detection, with up to 97% of mean Average Precision (mAP) and 0. 89 of F1-score when the weather was cloudy.

Domain-Specific NER via Retrieving Correlated Samples

1 code implementation COLING 2022 Xin Zhang, Yong Jiang, Xiaobin Wang, Xuming Hu, Yueheng Sun, Pengjun Xie, Meishan Zhang

Successful Machine Learning based Named Entity Recognition models could fail on texts from some special domains, for instance, Chinese addresses and e-commerce titles, where requires adequate background knowledge.

Named Entity Recognition

NET-FLEET: Achieving Linear Convergence Speedup for Fully Decentralized Federated Learning with Heterogeneous Data

no code implementations17 Aug 2022 Xin Zhang, Minghong Fang, Zhuqing Liu, Haibo Yang, Jia Liu, Zhengyuan Zhu

Moreover, whether or not the linear speedup for convergence is achievable under fully decentralized FL with data heterogeneity remains an open question.

Federated Learning

SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters

no code implementations17 Aug 2022 Zhuqing Liu, Xin Zhang, Jia Liu

To increase the training speed of distributed learning, recent years have witnessed a significant amount of interest in developing both synchronous and asynchronous distributed stochastic variance-reduced optimization methods.

Adaptive Domain Generalization via Online Disagreement Minimization

no code implementations3 Aug 2022 Xin Zhang, Ying-Cong Chen

Domain Generalization (DG) aims to safely transfer a model to unseen target domains by only relying on a set of source domains.

Domain Generalization

INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks

no code implementations27 Jul 2022 Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu

Our main contributions in this paper are two-fold: i) We first propose a deterministic algorithm called INTERACT (inner-gradient-descent-outer-tracked-gradient) that requires the sample complexity of $\mathcal{O}(n \epsilon^{-1})$ and communication complexity of $\mathcal{O}(\epsilon^{-1})$ to solve the bilevel optimization problem, where $n$ and $\epsilon > 0$ are the number of samples at each agent and the desired stationarity gap, respectively.

Bilevel Optimization Meta-Learning +1

Layer-Wise Partitioning and Merging for Efficient and Scalable Deep Learning

no code implementations22 Jul 2022 Samson B. Akintoye, Liangxiu Han, Huw Lloyd, Xin Zhang, Darren Dancey, Haoming Chen, Daoqiang Zhang

Deep Neural Network (DNN) models are usually trained sequentially from one layer to another, which causes forward, backward and update locking's problems, leading to poor performance in terms of training time.

Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey

no code implementations21 Jul 2022 Xian Tao, Xinyi Gong, Xin Zhang, Shaohua Yan, Chandranath Adak

This paper aims to help researchers in this field by comprehensively surveying recent achievements in unsupervised anomaly localization in industrial images using deep learning.

Gigapixel Whole-Slide Images Classification using Locally Supervised Learning

1 code implementation17 Jul 2022 Jingwei Zhang, Xin Zhang, Ke Ma, Rajarsi Gupta, Joel Saltz, Maria Vakalopoulou, Dimitris Samaras

Histopathology whole slide images (WSIs) play a very important role in clinical studies and serve as the gold standard for many cancer diagnoses.

Classification Multiple Instance Learning +1

A Coupling Enhancement Algorithm for ZrO2 Ceramic Bearing Ball Surface Defect Detection Based on Cartoon-texture Decomposition Model and Multi-Scale Filtering Method

no code implementations23 May 2022 Wei Wang, Xin Zhang, Jiaqi Yi, Xianqi Liao, Wenjie Li, Zhenhong Li

The experimental results show that the image denoising method of ZrO2 ceramic bearing ball surface defect based on cartoon-texture decomposition model can denoise while retaining the image details.

Defect Detection Image Denoising +1

Global Trajectory Helps Person Retrieval in a Camera Network

1 code implementation27 Apr 2022 Xin Zhang, Xiaohua Xie, JianHuang Lai, Wei-Shi Zheng

To address this problem, we propose a framework of person retrieval based on cross-camera trajectory generation which integrates both temporal and spatial information.

Person Retrieval Re-Ranking +1

Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations

1 code implementation ACL 2022 Xin Zhang, Guangwei Xu, Yueheng Sun, Meishan Zhang, Xiaobin Wang, Min Zhang

Recent works of opinion expression identification (OEI) rely heavily on the quality and scale of the manually-constructed training corpus, which could be extremely difficult to satisfy.

Contrastive-mixup learning for improved speaker verification

no code implementations22 Feb 2022 Xin Zhang, Minho Jin, Roger Cheng, Ruirui Li, Eunjung Han, Andreas Stolcke

In this work, we propose contrastive-mixup, a novel augmentation strategy that learns distinguishing representations based on a distance metric.

Data Augmentation Metric Learning +1

Priming Cross-Session Motor Imagery Classification with A Universal Deep Domain Adaptation Framework

no code implementations19 Feb 2022 Zhengqing Miao, Xin Zhang, Carlo Menon, Yelong Zheng, Meirong Zhao, Dong Ming

Compared to the vanilla EEGNet and ConvNet, the proposed SDDA framework was able to boost the MI classification accuracy by 15. 2%, 10. 2% respectively in IIA dataset, and 5. 5%, 4. 2% in IIB dataset.

Domain Adaptation Electroencephalogram (EEG)

Adaptive Graph Convolutional Networks for Weakly Supervised Anomaly Detection in Videos

no code implementations14 Feb 2022 Congqi Cao, Xin Zhang, Shizhou Zhang, Peng Wang, Yanning Zhang

For weakly supervised anomaly detection, most existing work is limited to the problem of inadequate video representation due to the inability of modeling long-term contextual information.

Association Graph Learning +1

Fast and Robust Sparsity Learning over Networks: A Decentralized Surrogate Median Regression Approach

no code implementations11 Feb 2022 Weidong Liu, Xiaojun Mao, Xin Zhang

Decentralized sparsity learning has attracted a significant amount of attention recently due to its rapidly growing applications.


TR-MISR: Multiimage Super-Resolution Based on Feature Fusion With Transformers

1 code implementation IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2022 Tai An, Xin Zhang, Chunlei Huo, Bin Xue, Lingfeng Wang, Chunhong Pan

In addition, TR-MISR adopts an additional learnable embedding vector that fuses these vectors to restore the details to the greatest extent. TR-MISR has successfully applied the transformer to MISR tasks for the first time, notably reducing the difficulty of training the transformer by ignoring the spatial relations of image patches.

Multi-Frame Super-Resolution

Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning

no code implementations NeurIPS 2021 Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu

To our knowledge, this paper is the first work that achieves both $\mathcal{O}(\epsilon^{-2})$ sample complexity and $\mathcal{O}(\epsilon^{-2})$ communication complexity in decentralized policy evaluation for cooperative MARL.

Multi-agent Reinforcement Learning Reinforcement Learning (RL) +1

Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains

1 code implementation25 Nov 2021 Xin Zhang, Shixiang Shane Gu, Yutaka Matsuo, Yusuke Iwasawa

We propose Domain Prompt Learning (DPL) as a novel approach for domain inference in the form of conditional prompt generation.

Domain Generalization Image Classification +2

Can depth-adaptive BERT perform better on binary classification tasks

no code implementations22 Nov 2021 Jing Fan, Xin Zhang, Sheng Zhang, Yan Pan, Lixiang Guo

In light of the success of transferring language models into NLP tasks, we ask whether the full BERT model is always the best and does it exist a simple but effective method to find the winning ticket in state-of-the-art deep neural networks without complex calculations.

Text Classification

CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Images

no code implementations20 Oct 2021 Xin Zhang, Liangxiu Han, Tam Sobeih, Lianghao Han, Nina Dempsey, Symeon Lechareas, Ascanio Tridente, Haoming Chen, Stephen White

The proposed method can provide more detailed high resolution visual explanation for the classification decision, compared to current state-of-the-art visual explanation methods and has a great potential to be used in clinical practice for COVID-19 pneumonia diagnosis.

Pneumonia Detection

Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks

no code implementations5 Oct 2021 Xin Zhang, Xiujun Shu, Bingwen Zhang, Jie Ren, Lizhou Zhou, Xin Chen

Deterministic models, such as ray tracing based on physical laws of wave propagation, are more accurate and site specific.

Stabilized Likelihood-based Imitation Learning via Denoising Continuous Normalizing Flow

no code implementations29 Sep 2021 Xin Zhang, Yanhua Li, Ziming Zhang, Christopher Brinton, Zhenming Liu, Zhi-Li Zhang, Hui Lu, Zhihong Tian

State-of-the-art imitation learning (IL) approaches, e. g, GAIL, apply adversarial training to minimize the discrepancy between expert and learner behaviors, which is prone to unstable training and mode collapse.

Denoising Imitation Learning

Anarchic Federated Learning

no code implementations23 Aug 2021 Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu

To satisfy the need for flexible worker participation, we consider a new FL paradigm called "Anarchic Federated Learning" (AFL) in this paper.

Federated Learning

Towards interpreting computer vision based on transformation invariant optimization

no code implementations18 Jun 2021 Chen Li, JinZhe Jiang, Xin Zhang, Tonghuan Zhang, YaQian Zhao, Dongdong Jiang, RenGang Li

Interpreting how does deep neural networks (DNNs) make predictions is a vital field in artificial intelligence, which hinders wide applications of DNNs.

Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition

1 code implementation ACL 2021 Xin Zhang, Guangwei Xu, Yueheng Sun, Meishan Zhang, Pengjun Xie

Crowdsourcing is regarded as one prospective solution for effective supervised learning, aiming to build large-scale annotated training data by crowd workers.

Domain Adaptation named-entity-recognition +3

Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain Adaptation

1 code implementation17 May 2021 Kelei He, Wen Ji, Tao Zhou, Zhuoyuan Li, Jing Huo, Xin Zhang, Yang Gao, Dinggang Shen, Bing Zhang, Junfeng Zhang

Specifically, a bidirectional image synthesis and segmentation module is proposed to segment the brain tumor using the intermediate data distributions generated for the two domains, which includes an image-to-image translator and a shared-weighted segmentation network.

Brain Tumor Segmentation Image Generation +2

GT-STORM: Taming Sample, Communication, and Memory Complexities in Decentralized Non-Convex Learning

no code implementations4 May 2021 Xin Zhang, Jia Liu, Zhengyuan Zhu, Elizabeth S. Bentley

Decentralized nonconvex optimization has received increasing attention in recent years in machine learning due to its advantages in system robustness, data privacy, and implementation simplicity.

Constructing long-short stock portfolio with a new listwise learn-to-rank algorithm

1 code implementation26 Apr 2021 Xin Zhang, Lan Wu, Zhixue Chen

Our loss function, motivated by the long-short strategy, is endogenously shift-invariant and can be viewed as a direct generalization of ListMLE.

Genetic Algorithm based hyper-parameters optimization for transfer Convolutional Neural Network

no code implementations26 Feb 2021 Chen Li, JinZhe Jiang, YaQian Zhao, RenGang Li, EnDong Wang, Xin Zhang, Kun Zhao

Decision of transfer layers and trainable layers is a major task for design of the transfer convolutional neural networks (CNN).

Hyperparameter Optimization

Constraints on interacting dark energy models from time-delay cosmography with seven lensed quasars

no code implementations18 Feb 2021 Ling-Feng Wang, Dong-Ze He, Jing-Fei Zhang, Xin Zhang

When the TD data are added to the CMB$+$BAO$+$SN$+H_0$ data, we find that: (i) the coupling parameter $\beta$ in all the considered IDE models is positive within 1$\sigma$ range, implying a mild preference for the case of cold dark matter decaying into dark energy; (ii) the IDE model with $Q = \beta H_{0} \rho_{\rm c}$ slightly relieves the $S_8$ tension, but the other considered IDE models further aggravate this tension; (iii) the Akaike information criteria of the IDE models with $Q \propto \rho_{\rm c}$ are lower than that of the $\Lambda$CDM model, indicating that these IDE models are more preferred by the current mainstream data.

Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Phenomenology

Phantom Bethe roots in the integrable open spin $1/2$ $XXZ$ chain

no code implementations5 Feb 2021 Xin Zhang, Andreas Klümper, Vladislav Popkov

Bethe eigenstates are described by two complementary sets of Bethe Ansatz equations for regular roots, one for each invariant subspace.

Statistical Mechanics Mathematical Physics Mathematical Physics Quantum Physics

Phantom Bethe excitations and spin helix eigenstates in integrable periodic and open spin chains

no code implementations5 Feb 2021 Vladislav Popkov, Xin Zhang, Andreas Klümper

The phantom Bethe roots lead to degeneracies between different magnetization sectors in the periodic case and to the appearance of spin helix states (SHS), i. e. periodically modulated states of chiral nature in both open and closed systems.

Statistical Mechanics Mathematical Physics Mathematical Physics Quantum Physics

Relieving the $H_0$ tension with a new interacting dark energy model

no code implementations26 Jan 2021 Li-Yang Gao, She-Sheng Xue, Xin Zhang

Here we explain this model as a scenario of vacuum energy interacting with matter and radiation.

Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Phenomenology

Designing 24-hour Electrical Power Generator: Thermoradiative Device for Harvesting Energy from Sun and Outer Space

no code implementations14 Jan 2021 Xin Zhang, Guofeng Yang, Mengqi Yan, Lay Kee Ang, Yee Sin Ang

Energy harvesting from sun and outer space using thermoradiative devices (TRD), despite being promising renewable energy sources, are limited only to daytime and nighttime period, respectively.

Applied Physics Mesoscale and Nanoscale Physics

Spectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

no code implementations7 Jan 2021 Xingchen Zhou, Yan Gong, Xian-Min Meng, Xin Zhang, Ye Cao, Xuelei Chen, Valeria Amaro, Zuhui Fan, Liping Fu

This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys.

Photometric Redshift Estimation Cosmology and Nongalactic Astrophysics

Super strong paramagnetism of aromatic peptides adsorbed with monovalent cations

no code implementations22 Dec 2020 Shiqi Sheng, Haijun Yang, Liuhua Mu, Zixin Wang, Jihong Wang, Peng Xiu, Jun Hu, Xin Zhang, Feng Zhang, Haiping Fang

We experimentally demonstrated that the AYFFF self-assemblies adsorbed with various monovalent cations (Na+, K+, and Li+) show unexpectedly super strong paramagnetism.

Biological Physics

K-core in percolated dense graph sequences

no code implementations17 Dec 2020 Erhan Bayraktar, Suman Chakraborty, Xin Zhang

Keeping an edge $(i, j)$ of $G_n$ with probability $\min \{ {a^n_{i, j}}/{n}, 1 \}$ independently, we obtain a sequence of random graphs $G_n(\frac{1}{n})$.

Probability Combinatorics

f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning

no code implementations NeurIPS 2020 Xin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang

This naturally gives rise to the following question: Given a set of expert demonstrations, which divergence can recover the expert policy more accurately with higher data efficiency?

Imitation Learning

Prediction against a limited adversary

no code implementations31 Oct 2020 Erhan Bayraktar, Ibrahim Ekren, Xin Zhang

We study the problem of prediction with expert advice with adversarial corruption where the adversary can at most corrupt one expert.

$f$-GAIL: Learning $f$-Divergence for Generative Adversarial Imitation Learning

1 code implementation2 Oct 2020 Xin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang

This naturally gives rise to the following question: Given a set of expert demonstrations, which divergence can recover the expert policy more accurately with higher data efficiency?

Imitation Learning

Worst-Case-Aware Curriculum Learning for Zero and Few Shot Transfer

1 code implementation23 Sep 2020 Sheng Zhang, Xin Zhang, Weiming Zhang, Anders Søgaard

Multi-task transfer learning based on pre-trained language encoders achieves state-of-the-art performance across a range of tasks.

Transfer Learning

An Explainable 3D Residual Self-Attention Deep Neural Network FOR Joint Atrophy Localization and Alzheimer's Disease Diagnosis using Structural MRI

no code implementations10 Aug 2020 Xin Zhang, Liangxiu Han, Wenyong Zhu, Liang Sun, Daoqiang Zhang

Different from the existing approaches, the novelty of our approach is three-fold: 1) A Residual Self-Attention Deep Neural Network has been proposed to capture local, global and spatial information of MR images to improve diagnostic performance; 2) An explanation method using Gradient-based Localization Class Activation mapping (Grad-CAM) has been introduced to improve the explainable of the proposed method; 3) This work has provided a full end-to-end learning solution for automated disease diagnosis.


A Computer Vision Based Beamforming Scheme for Millimeter Wave Communication in LOS Scenarios

no code implementations20 Jun 2020 Tianqi Xiang, Yaxin Wang, Huiwen Li, Boren Guo, Xin Zhang

A novel location-aware beamforming scheme for millimeter wave communication is proposed for line of sight (LOS) and low mobility scenarios, in which computer vision is introduced to derive the required position or spatial angular information from the image or video captured by camera(s) co-located with mmWave antenna array at base stations.

A study of the effect of the illumination model on the generation of synthetic training datasets

no code implementations15 Jun 2020 Xin Zhang, Ning Jia, Ioannis Ivrissimtzis

Our results show that the effect of the illumination model is important, comparable in significance to the network architecture.

A Computer Vision Aided Beamforming Scheme with EM Exposure Control in Outdoor LOS Scenarios

no code implementations14 Jun 2020 Tianqi Xiang, Huiwen Li, Boren Guo, Xin Zhang

The proposed exposure avoidance method is validated in simulations, and the results show that the finer beam management granularity can guarantee communication quality while reducing the electromagnetic exposure.


Generalization Study of Quantum Neural Network

no code implementations2 Jun 2020 JinZhe Jiang, Xin Zhang, Chen Li, YaQian Zhao, RenGang Li

In this model, we mapped the feature data to a quantum state in Hilbert space firstly, and then implement unitary evolution on it, in the end, we can get the classification result by im-plement measurement on the quantum state.

HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation

no code implementations21 May 2020 Kelei He, Chunfeng Lian, Bing Zhang, Xin Zhang, Xiaohuan Cao, Dong Nie, Yang Gao, Junfeng Zhang, Dinggang Shen

In this paper, we tackle the challenging task of prostate segmentation in CT images by a two-stage network with 1) the first stage to fast localize, and 2) the second stage to accurately segment the prostate.

Multi-Task Learning

Malicious Experts versus the multiplicative weights algorithm in online prediction

no code implementations18 Mar 2020 Erhan Bayraktar, H. Vincent Poor, Xin Zhang

We assume that one of the experts is honest and makes correct prediction with probability $\mu$ at each round.

Complexity of tree-coloring interval graphs equitably

no code implementations9 Mar 2020 Bei Niu, Bi Li, Xin Zhang

An equitable tree-$k$-coloring of a graph is a vertex $k$-coloring such that each color class induces a forest and the size of any two color classes differ by at most one.

Combinatorics Discrete Mathematics

Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach

no code implementations12 Jan 2020 Xin Zhang, Minghong Fang, Jia Liu, Zhengyuan Zhu

In this paper, we consider the problem of jointly improving data privacy and communication efficiency of distributed edge learning, both of which are critical performance metrics in wireless edge network computing.

ResNetX: a more disordered and deeper network architecture

no code implementations18 Dec 2019 Wenfeng Feng, Xin Zhang, Guangpeng Zhao

Our architecture is a natural extension to ResNet, and can be integrated with existing state-of-the-art methods with little effort.

Image Classification

Finite-Time 4-Expert Prediction Problem

no code implementations22 Nov 2019 Erhan Bayraktar, Ibrahim Ekren, Xin Zhang

We explicitly solve the nonlinear PDE that is the continuous limit of dynamic programming of \emph{expert prediction problem} in finite horizon setting with $N=4$ experts.

Blockchain for Future Smart Grid: A Comprehensive Survey

1 code implementation8 Nov 2019 Muhammad Baqer Mollah, Jun Zhao, Dusit Niyato, Kwok-Yan Lam, Xin Zhang, Amer M. Y. M. Ghias, Leong Hai Koh, Lei Yang

In this paper, we aim to provide a comprehensive survey on application of blockchain in smart grid.

Cryptography and Security Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Social and Information Networks Systems and Control Systems and Control

Spectrogram-frame linear network and continuous frame sequence for bird sound classification

1 code implementation Ecological Informatics 2019 Xin Zhang, Aibin Chen, Guoxiong Zhou, Zhiqiang Zhang, Xibei Huang, Xiaohu Qiang

Inspired by that bird sound has various frequency distributions and continuous time-varying properties, a novel method is proposed for the classification of bird sound based on continuous frame sequence and spectrogram-frame linear network (SFLN).

Air-Writing Translater: A Novel Unsupervised Domain Adaptation Method for Inertia-Trajectory Translation of In-air Handwriting

no code implementations1 Nov 2019 Songbin Xu, Yang Xue, Xin Zhang, Lianwen Jin

As a new way of human-computer interaction, inertial sensor based in-air handwriting can provide a natural and unconstrained interaction to express more complex and richer information in 3D space.

Translation Unsupervised Domain Adaptation


no code implementations25 Sep 2019 Xin Zhang, Weixiao Huang, Renjie Liao, Yanhua Li

Imitation learning aims to inversely learn a policy from expert demonstrations, which has been extensively studied in the literature for both single-agent setting with Markov decision process (MDP) model, and multi-agent setting with Markov game (MG) model.

Imitation Learning

PolSAR Image Classification Based on Dilated Convolution and Pixel-Refining Parallel Mapping network in the Complex Domain

1 code implementation24 Sep 2019 Dongling Xiao, Chang Liu, Qi. Wang, Chao Wang, Xin Zhang

For general supervised deep learning classification algorithms, the pixel-by-pixel algorithm achieves precise yet inefficient classification with a small number of labeled pixels, whereas the pixel mapping algorithm achieves efficient yet edge-rough classification with more prior labels required.

Classification General Classification +1

Byzantine-Resilient Stochastic Gradient Descent for Distributed Learning: A Lipschitz-Inspired Coordinate-wise Median Approach

no code implementations10 Sep 2019 Haibo Yang, Xin Zhang, Minghong Fang, Jia Liu

In this work, we consider the resilience of distributed algorithms based on stochastic gradient descent (SGD) in distributed learning with potentially Byzantine attackers, who could send arbitrary information to the parameter server to disrupt the training process.

Neural Machine Reading Comprehension: Methods and Trends

no code implementations2 Jul 2019 Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang

Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques over the past few years.

Machine Reading Comprehension

Machine Reading Comprehension: a Literature Review

no code implementations30 Jun 2019 Xin Zhang, An Yang, Sujian Li, Yizhong Wang

Machine reading comprehension aims to teach machines to understand a text like a human and is a new challenging direction in Artificial Intelligence.

Machine Reading Comprehension

Distributed Linear Model Clustering over Networks: A Tree-Based Fused-Lasso ADMM Approach

no code implementations28 May 2019 Xin Zhang, Jia Liu, Zhengyuan Zhu

In this work, we consider to improve the model estimation efficiency by aggregating the neighbors' information as well as identify the subgroup membership for each node in the network.

Watermark retrieval from 3D printed objects via synthetic data training

no code implementations23 May 2019 Xin Zhang, Ning Jia, Ioannis Ivrissimtzis

We conclude that in our application domain of information retrieval from 3D printed objects, where access to the exact CAD files of the printed objects can be assumed, one can use inexpensive synthetic data to enhance neural network training, reducing the need for the labour intensive process of creating large amounts of hand labelled real data or the need to generate photorealistic synthetic data.

Information Retrieval Retrieval

Spatial CUSUM for Signal Region Detection

no code implementations5 Apr 2019 Xin Zhang, Zhengyuan Zhu

We develop theoretical properties of the method which indicates that asymptotically SCUSUM can reach high classification accuracy.


The Random Conditional Distribution for Higher-Order Probabilistic Inference

no code implementations25 Mar 2019 Zenna Tavares, Xin Zhang, Edgar Minaysan, Javier Burroni, Rajesh Ranganath, Armando Solar Lezama

The need to condition distributional properties such as expectation, variance, and entropy arises in algorithmic fairness, model simplification, robustness and many other areas.

Fairness Probabilistic Programming

On-line Search History-assisted Restart Strategy for Covariance Matrix Adaptation Evolution Strategy

no code implementations16 Mar 2019 Yang Lou, Shiu Yin Yuen, Guanrong Chen, Xin Zhang

The entire on-line search history of cNrGA is stored in a binary space partitioning (BSP) tree, which is effective for performing local search.

Probabilistic Verification of Fairness Properties via Concentration

1 code implementation2 Dec 2018 Osbert Bastani, Xin Zhang, Armando Solar-Lezama

As machine learning systems are increasingly used to make real world legal and financial decisions, it is of paramount importance that we develop algorithms to verify that these systems do not discriminate against minorities.

BIG-bench Machine Learning Fairness

Skeleton-based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Module

1 code implementation17 Nov 2018 Chenyang Li, Xin Zhang, Lufan Liao, Lianwen Jin, Weixin Yang

In this paper, we first leverage a robust feature descriptor, path signature (PS), and propose three PS features to explicitly represent the spatial and temporal motion characteristics, i. e., spatial PS (S_PS), temporal PS (T_PS) and temporal spatial PS (T_S_PS).

General Classification Gesture Recognition

Taming Convergence for Asynchronous Stochastic Gradient Descent with Unbounded Delay in Non-Convex Learning

no code implementations24 May 2018 Xin Zhang, Jia Liu, Zhengyuan Zhu

Understanding the convergence performance of asynchronous stochastic gradient descent method (Async-SGD) has received increasing attention in recent years due to their foundational role in machine learning.

Land use mapping in the Three Gorges Reservoir Area based on semantic segmentation deep learning method

no code implementations18 Mar 2018 Xin Zhang, Bingfang Wu, Liang Zhu, Fuyou Tian, Miao Zhang, Yuanzeng

In this paper, we first test the state of the art semantic segmentation deep learning classifiers for LUCC mapping with 7 categories in the TGRA area with rapideye 5m resolution data.

Semantic Segmentation

Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections

no code implementations NeurIPS 2018 Xin Zhang, Armando Solar-Lezama, Rishabh Singh

We argue that such a correction is a useful way to provide feedback to a user when the network's output is different from a desired output.

Aspect-level Sentiment Classification with HEAT (HiErarchical ATtention) Network

no code implementations CIKM 2017 Jiajun Cheng, Shenglin Zhao, Jiani Zhang, Irwin King, Xin Zhang, Hui Wang

However, the prior work only attends to the sentiment information and ignores the aspect-related information in the text, which may cause mismatching between the sentiment words and the aspects when an unrelated sentiment word is semantically meaningful for the given aspect.

Sentiment Analysis Sentiment Classification

Learning Multi-level Features For Sensor-based Human Action Recognition

no code implementations22 Nov 2016 Yan Xu, Zhengyang Shen, Xin Zhang, Yifan Gao, Shujian Deng, Yipei Wang, Yubo Fan, Eric I-Chao Chang

This paper proposes a multi-level feature learning framework for human action recognition using a single body-worn inertial sensor.

Action Recognition Temporal Action Localization

Blocking Collapsed Gibbs Sampler for Latent Dirichlet Allocation Models

no code implementations2 Aug 2016 Xin Zhang, Scott A. Sisson

In this article, we introduce a blocking scheme to the collapsed Gibbs sampler for the LDA model which can, with a theoretical guarantee, improve chain mixing efficiency.

End to End Learning for Self-Driving Cars

114 code implementations25 Apr 2016 Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, Karol Zieba

The system automatically learns internal representations of the necessary processing steps such as detecting useful road features with only the human steering angle as the training signal.

Lane Detection Self-Driving Cars

Dynamic Structure Embedded Online Multiple-Output Regression for Stream Data

no code implementations18 Dec 2014 Changsheng Li, Fan Wei, Weishan Dong, Qingshan Liu, Xiangfeng Wang, Xin Zhang

MORES can \emph{dynamically} learn the structure of the coefficients change in each update step to facilitate the model's continuous refinement.


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