Search Results for author: Wei Chen

Found 294 papers, 82 papers with code

Combinatorial Pure Exploration for Dueling Bandit

no code implementations ICML 2020 Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

For Borda winner, we establish a reduction of the problem to the original CPE-MAB setting and design PAC and exact algorithms that achieve both the sample complexity similar to that in the CPE-MAB setting (which is nearly optimal for a subclass of problems) and polynomial running time per round.

A Structure-Aware Argument Encoder for Literature Discourse Analysis

1 code implementation COLING 2022 Yinzi Li, Wei Chen, Zhongyu Wei, Yujun Huang, Chujun Wang, Siyuan Wang, Qi Zhang, Xuanjing Huang, Libo Wu

Existing research for argument representation learning mainly treats tokens in the sentence equally and ignores the implied structure information of argumentative context.

Representation Learning

Dual Refinement Underwater Object Detection Network

1 code implementation ECCV 2020 Baojie Fan, Wei Chen, Yang Cong, Jiandong Tian

Due to the complex underwater environment, underwater imaging often encounters some problems such as blur, scale variation, color shift, and texture distortion.

object-detection Object Detection

Combinatorial Causal Bandits without Graph Skeleton

no code implementations31 Jan 2023 Shi Feng, Nuoya Xiong, Wei Chen

This paper studies the CCB problem without the graph structure on binary general causal models and BGLMs.

Does Federated Learning Really Need Backpropagation?

1 code implementation28 Jan 2023 Haozhe Feng, Tianyu Pang, Chao Du, Wei Chen, Shuicheng Yan, Min Lin

BAFFLE is 1) memory-efficient and easily fits uploading bandwidth; 2) compatible with inference-only hardware optimization and model quantization or pruning; and 3) well-suited to trusted execution environments, because the clients in BAFFLE only execute forward propagation and return a set of scalars to the server.

Federated Learning Quantization

XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis

no code implementations25 Jan 2023 Yingchaojie Feng, Xingbo Wang, Bo Pan, Kam Kwai Wong, Yi Ren, Shi Liu, Zihan Yan, Yuxin Ma, Huamin Qu, Wei Chen

Our research explores how to provide explanations for NLIs to help users locate the problems and further revise the queries.

Data Visualization

Elevation Estimation-Driven Building 3D Reconstruction from Single-View Remote Sensing Imagery

no code implementations11 Jan 2023 Yongqiang Mao, Kaiqiang Chen, Liangjin Zhao, Wei Chen, Deke Tang, Wenjie Liu, Zhirui Wang, Wenhui Diao, Xian Sun, Kun fu

Our Building3D is rooted in the SFFDE network for building elevation prediction, synchronized with a building extraction network for building masks, and then sequentially performs point cloud reconstruction, surface reconstruction (or CityGML model reconstruction).

Point cloud reconstruction Surface Reconstruction

Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces

no code implementations11 Jan 2023 Zhu Liang, Matthew R. Carbone, Wei Chen, Fanchen Meng, Eli Stavitski, Deyu Lu, Mark S. Hybertsen, Xiaohui Qu

A new semi-supervised machine learning method for the discovery of structure-spectrum relationships is developed and demonstrated using the specific example of interpreting X-ray absorption near-edge structure (XANES) spectra.

MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding

2 code implementations2 Jan 2023 Steven H. Wang, Antoine Scardigli, Leonard Tang, Wei Chen, Dimitry Levkin, Anya Chen, Spencer Ball, Thomas Woodside, Oliver Zhang, Dan Hendrycks

Reading comprehension of legal text can be a particularly challenging task due to the length and complexity of legal clauses and a shortage of expert-annotated datasets.

Reading Comprehension

Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks

no code implementations21 Dec 2022 Rusheng Pan, Zhiyong Wang, Yating Wei, Han Gao, Gongchang Ou, Caleb Chen Cao, Jingli Xu, Tong Xu, Wei Chen

A computational graph in a deep neural network (DNN) denotes a specific data flow diagram (DFD) composed of many tensors and operators.

Category-Level 6D Object Pose Estimation with Flexible Vector-Based Rotation Representation

no code implementations9 Dec 2022 Wei Chen, Xi Jia, Zhongqun Zhang, Hyung Jin Chang, Linlin Shen, Jinming Duan, Ales Leonardis

The proposed rotation representation has two major advantages: 1) decoupled characteristic that makes the rotation estimation easier; 2) flexible length and rotated angle of the vectors allow us to find a more suitable vector representation for specific pose estimation task.

6D Pose Estimation using RGB Data Augmentation

CSI-PPPNet: A One-Sided Deep Learning Framework for Massive MIMO CSI Feedback

no code implementations29 Nov 2022 Wei Chen, Weixiao Wan, Shiyue Wang, Peng Sun, Bo Ai

This paper presents a novel method for massive MIMO CSI feedback via a one-sided deep learning framework.

Denoising

Fourier-Net: Fast Image Registration with Band-limited Deformation

1 code implementation29 Nov 2022 Xi Jia, Joseph Bartlett, Wei Chen, Siyang Song, Tianyang Zhang, Xinxing Cheng, Wenqi Lu, Zhaowen Qiu, Jinming Duan

Specifically, instead of our Fourier-Net learning to output a full-resolution displacement field in the spatial domain, we learn its low-dimensional representation in a band-limited Fourier domain.

Image Registration

A Knowledge-based Learning Framework for Self-supervised Pre-training Towards Enhanced Recognition of Biomedical Microscopy Images

1 code implementation27 Nov 2022 Wei Chen, Chen Li, Dan Chen, Xin Luo

Self-supervised pre-training has become the priory choice to establish reliable neural networks for automated recognition of massive biomedical microscopy images, which are routinely annotation-free, without semantics, and without guarantee of quality.

Contrastive Learning Image Restoration +2

ElegantSeg: End-to-End Holistic Learning for Extra-Large Image Semantic Segmentation

no code implementations21 Nov 2022 Wei Chen, Yansheng Li, Bo Dang, Yongjun Zhang

This paper presents a new paradigm for Extra-large image semantic Segmentation, called ElegantSeg, that capably processes holistic extra-large image semantic segmentation (ELISS).

Semantic Segmentation

ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data

1 code implementation15 Nov 2022 Hengrui Zhang, Wei Wayne Chen, James M. Rondinelli, Wei Chen

To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems.

Active Learning

Synchronization of Diverse Agents via Phase Analysis

no code implementations8 Nov 2022 Dan Wang, Wei Chen, Li Qiu

They can also model the controllers of the agents which may be different for each agent or uniform for all the agents.

Fully Bayesian inference for latent variable Gaussian process models

no code implementations4 Nov 2022 Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley

However, this plug-in approach will not account for uncertainty in estimation of the LVs, which can be significant especially with limited training data.

Bayesian Inference Gaussian Processes

Global-to-local Expression-aware Embeddings for Facial Action Unit Detection

no code implementations27 Oct 2022 Rudong An, Wei zhang, Hao Zeng, Wei Chen, Zhigang Deng, Yu Ding

Then, AU feature maps and their corresponding AU masks are multiplied to generate AU masked features focusing on local facial region.

Action Unit Detection Facial Action Unit Detection

Facial Action Units Detection Aided by Global-Local Expression Embedding

no code implementations25 Oct 2022 Zhipeng Hu, Wei zhang, Lincheng Li, Yu Ding, Wei Chen, Zhigang Deng, Xin Yu

We find that AUs and facial expressions are highly associated, and existing facial expression datasets often contain a large number of identities.

3D Face Reconstruction

Feature-Proxy Transformer for Few-Shot Segmentation

2 code implementations13 Oct 2022 Jian-Wei Zhang, Yifan Sun, Yi Yang, Wei Chen

With a rethink of recent advances, we find that the current FSS framework has deviated far from the supervised segmentation framework: Given the deep features, FSS methods typically use an intricate decoder to perform sophisticated pixel-wise matching, while the supervised segmentation methods use a simple linear classification head.

Few-Shot Semantic Segmentation Semantic Segmentation

Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control

no code implementations4 Oct 2022 Zixuan Zhang, Yuning Jiang, Yuanming Shi, Ye Shi, Wei Chen

This paper develops an optimal EV charging/discharging control strategy for different EV users under dynamic environments to maximize EV users' benefits.

reinforcement-learning reinforcement Learning

Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models

1 code implementation14 Sep 2022 Chen Wu, Ruqing Zhang, Jiafeng Guo, Wei Chen, Yixing Fan, Maarten de Rijke, Xueqi Cheng

A ranking model is said to be Certified Top-$K$ Robust on a ranked list when it is guaranteed to keep documents that are out of the top $K$ away from the top $K$ under any attack.

Information Retrieval Retrieval

MMKGR: Multi-hop Multi-modal Knowledge Graph Reasoning

no code implementations3 Sep 2022 Shangfei Zheng, Weiqing Wang, Jianfeng Qu, Hongzhi Yin, Wei Chen, Lei Zhao

Multi-modal knowledge graphs (MKGs) include not only the relation triplets, but also related multi-modal auxiliary data (i. e., texts and images), which enhance the diversity of knowledge.

Knowledge Graphs Missing Elements +1

Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction

1 code implementation3 Sep 2022 Yufeng Zhang, Weiqing Wang, Hongzhi Yin, Pengpeng Zhao, Wei Chen, Lei Zhao

A more challenging scenario is that emerging KGs consist of only unseen entities, called as disconnected emerging KGs (DEKGs).

Contrastive Learning Inductive Link Prediction +1

Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms

no code implementations31 Aug 2022 Xutong Liu, Jinhang Zuo, Siwei Wang, Carlee Joe-Wong, John C. S. Lui, Wei Chen

Under this new condition, we propose a BCUCB-T algorithm with variance-aware confidence intervals and conduct regret analysis which reduces the $O(K)$ factor to $O(\log K)$ or $O(\log^2 K)$ in the regret bound, significantly improving the regret bounds for the above applications.

A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis

1 code implementation COLING 2022 Wei Chen, Jinglong Du, Zhao Zhang, Fuzhen Zhuang, Zhongshi He

Recently, some span-based methods have achieved encouraging performances for joint aspect-sentiment analysis, which first extract aspects (aspect extraction) by detecting aspect boundaries and then classify the span-level sentiments (sentiment classification).

Aspect Extraction Sentiment Analysis

Provable Adaptivity in Adam

no code implementations21 Aug 2022 Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen

In particular, the existing analysis of Adam cannot clearly demonstrate the advantage of Adam over SGD.

Global Consistent Point Cloud Registration Based on Lie-algebraic Cohomology

no code implementations15 Aug 2022 Yuxue Ren, Baowei Jiang, Wei Chen, Na lei, Xianfeng David Gu

We present a novel, effective method for global point cloud registration problems by geometric topology.

Point Cloud Registration

D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights

1 code implementation21 Jul 2022 Yuzhen Zhang, Wentong Wang, Weizhi Guo, Pei Lv, Mingliang Xu, Wei Chen, Dinesh Manocha

We present a trajectory prediction approach with respect to traffic lights, D2-TPred, which uses a spatial dynamic interaction graph (SDG) and a behavior dependency graph (BDG) to handle the problem of discontinuous dependency in the spatial-temporal space.

Trajectory Prediction

Uncertainty-Aware Mixed-Variable Machine Learning for Materials Design

no code implementations11 Jul 2022 Hengrui Zhang, Wei Wayne Chen, Akshay Iyer, Daniel W. Apley, Wei Chen

Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods.

BIG-bench Machine Learning

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization

no code implementations27 Jun 2022 Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu

By ensuring differential privacy in the learning algorithms, one can rigorously mitigate the risk of large models memorizing sensitive training data.

Combinatorial Pure Exploration of Causal Bandits

no code implementations16 Jun 2022 Nuoya Xiong, Wei Chen

The combinatorial pure exploration of causal bandits is the following online learning task: given a causal graph with unknown causal inference distributions, in each round we choose a subset of variables to intervene or do no intervention, and observe the random outcomes of all random variables, with the goal that using as few rounds as possible, we can output an intervention that gives the best (or almost best) expected outcome on the reward variable $Y$ with probability at least $1-\delta$, where $\delta$ is a given confidence level.

Causal Inference Multi-Armed Bandits

Combinatorial Causal Bandits

1 code implementation4 Jun 2022 Shi Feng, Wei Chen

For the special case of linear models with hidden variables, we apply causal inference techniques such as the do-calculus to convert the original model into a Markovian model, and then show that our BGLM-OFU algorithm and another algorithm based on the linear regression both solve such linear models with hidden variables.

Causal Inference

Tiered Reinforcement Learning: Pessimism in the Face of Uncertainty and Constant Regret

1 code implementation25 May 2022 Jiawei Huang, Li Zhao, Tao Qin, Wei Chen, Nan Jiang, Tie-Yan Liu

We propose a new learning framework that captures the tiered structure of many real-world user-interaction applications, where the users can be divided into two groups based on their different tolerance on exploration risks and should be treated separately.

reinforcement-learning reinforcement Learning

Mutual Distillation Learning Network for Trajectory-User Linking

1 code implementation8 May 2022 Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong

In this paper, we propose a novel Mutual distillation learning network to solve the TUL problem for sparse check-in mobility data, named MainTUL.

DxFormer: A Decoupled Automatic Diagnostic System Based on Decoder-Encoder Transformer with Dense Symptom Representations

1 code implementation8 May 2022 Wei Chen, Cheng Zhong, Jiajie Peng, Zhongyu Wei

Diagnosis-oriented dialogue system queries the patient's health condition and makes predictions about possible diseases through continuous interaction with the patient.

Text Generation

Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance

no code implementations7 May 2022 Zijian Li, Ruichu Cai, Jiawei Chen, Yuguan Yan, Wei Chen, Keli Zhang, Junjian Ye

Based on this inspiration, we investigate the domain-invariant unweighted sparse associative structures and the domain-variant strengths of the structures.

Time Series Unsupervised Domain Adaptation

A Benchmark for Automatic Medical Consultation System: Frameworks, Tasks and Datasets

1 code implementation19 Apr 2022 Wei Chen, Zhiwei Li, Hongyi Fang, Qianyuan Yao, Cheng Zhong, Jianye Hao, Qi Zhang, Xuanjing Huang, Jiajie Peng, Zhongyu Wei

In recent years, interest has arisen in using machine learning to improve the efficiency of automatic medical consultation and enhance patient experience.

Dialogue Act Classification Dialogue Understanding +3

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs

1 code implementation13 Apr 2022 Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu

Stochastic partial differential equations (SPDEs) are significant tools for modeling dynamics in many areas including atmospheric sciences and physics.

Automated Sleep Staging via Parallel Frequency-Cut Attention

1 code implementation7 Apr 2022 Zheng Chen, Ziwei Yang, Lingwei Zhu, Wei Chen, Toshiyo Tamura, Naoaki Ono, MD Altaf-Ul-Amin, Shigehiko Kanaya, Ming Huang

This paper proposes a novel framework for automatically capturing the time-frequency nature of electroencephalogram (EEG) signals of human sleep based on the authoritative sleep medicine guidance.

Decision Making EEG +2

TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed

1 code implementation CVPR 2022 Shian Du, Yihong Luo, Wei Chen, Jian Xu, Delu Zeng

In this paper, a temporal optimization is proposed by optimizing the evolutionary time for forward propagation of the neural ODE training.

t-METASET: Tailoring Property Bias of Large-Scale Metamaterial Datasets through Active Learning

no code implementations21 Feb 2022 Doksoo Lee, Yu-Chin Chan, Wei Wayne Chen, LiWei Wang, Anton van Beek, Wei Chen

Distinctly, we seek a solution to a commonplace yet frequently overlooked scenario at early stages of data-driven design of metamaterials: when a massive (~O(10^4 )) shape-only library has been prepared with no properties evaluated.

Active Learning

GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty

1 code implementation21 Feb 2022 Wei Wayne Chen, Doksoo Lee, Oluwaseyi Balogun, Wei Chen

To address this issue, we propose a Generative Adversarial Network-based Design under Uncertainty Framework (GAN-DUF), which contains a deep generative model that simultaneously learns a compact representation of nominal (ideal) designs and the conditional distribution of fabricated designs given any nominal design.

Robust Design

Branching Reinforcement Learning

no code implementations16 Feb 2022 Yihan Du, Wei Chen

In this paper, we propose a novel Branching Reinforcement Learning (Branching RL) model, and investigate both Regret Minimization (RM) and Reward-Free Exploration (RFE) metrics for this model.

Recommendation Systems reinforcement-learning +1

When Small Gain Meets Small Phase

no code implementations16 Jan 2022 Di Zhao, Wei Chen, Li Qiu

In this paper, we investigate the feedback stability of multiple-input multiple-output linear time-invariant systems with combined gain and phase information.

REST: Debiased Social Recommendation via Reconstructing Exposure Strategies

1 code implementation13 Jan 2022 Ruichu Cai, Fengzhu Wu, Zijian Li, Jie Qiao, Wei Chen, Yuexing Hao, Hao Gu

By explicitly Reconstructing Exposure STrategies (REST in short), we formalize the recommendation problem as the counterfactual reasoning and propose the debiased social recommendation method.

Selection bias

Baihe: SysML Framework for AI-driven Databases

no code implementations29 Dec 2021 Andreas Pfadler, Rong Zhu, Wei Chen, Botong Huang, Tianjing Zeng, Bolin Ding, Jingren Zhou

Based on the high level architecture, we then describe a concrete implementation of Baihe for PostgreSQL and present example use cases for learned query optimizers.

Deep Generative Models for Geometric Design Under Uncertainty

1 code implementation15 Dec 2021 Wei Wayne Chen, Doksoo Lee, Wei Chen

Deep generative models have demonstrated effectiveness in learning compact and expressive design representations that significantly improve geometric design optimization.

Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size

no code implementations7 Dec 2021 Rong Zhu, Tianjing Zeng, Andreas Pfadler, Wei Chen, Bolin Ding, Jingren Zhou

Cardinality estimation (CardEst), a central component of the query optimizer, plays a significant role in generating high-quality query plans in DBMS.

Remixing Functionally Graded Structures: Data-Driven Topology Optimization with Multiclass Shape Blending

1 code implementation1 Dec 2021 Yu-Chin Chan, Daicong Da, LiWei Wang, Wei Chen

We propose to inherit the advantages of both through a data-driven framework for multiclass functionally graded structures that mixes several families, i. e., classes, of microstructure topologies to create spatially-varying designs with guaranteed feasibility.

Recovering Latent Causal Factor for Generalization to Distributional Shifts

1 code implementation NeurIPS 2021 Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu

To avoid such a spurious correlation, we propose \textbf{La}tent \textbf{C}ausal \textbf{I}nvariance \textbf{M}odels (LaCIM) that specifies the underlying causal structure of the data and the source of distributional shifts, guiding us to pursue only causal factor for prediction.

CCSL: A Causal Structure Learning Method from Multiple Unknown Environments

no code implementations18 Nov 2021 Wei Chen, Yunjin Wu, Ruichu Cai, Yueguo Chen, Zhifeng Hao

Specifically, for the former, we provide a Causality-related Chinese Restaurant Process to cluster samples based on the similarity of the causal structure; for the latter, we introduce a variational-inference-based approach to learn the causal structures.

Causal Discovery Variational Inference

The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle

no code implementations NeurIPS 2021 Fang Kong, Yueran Yang, Wei Chen, Shuai Li

These are the first theoretical results for TS to solve CMAB with a common approximation oracle and break the misconception that TS cannot work with approximation oracles.

Combinatorial Optimization Thompson Sampling

Availability Attacks Create Shortcuts

1 code implementation1 Nov 2021 Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

We are the first to unveil an important population property of the perturbations of these attacks: they are almost \textbf{linearly separable} when assigned with the target labels of the corresponding samples, which hence can work as \emph{shortcuts} for the learning objective.

Data Poisoning

Collaborative Pure Exploration in Kernel Bandit

no code implementations29 Oct 2021 Yihan Du, Wei Chen, Yuko Kuroki, Longbo Huang

In this paper, we formulate a Collaborative Pure Exploration in Kernel Bandit problem (CoPE-KB), which provides a novel model for multi-agent multi-task decision making under limited communication and general reward functions, and is applicable to many online learning tasks, e. g., recommendation systems and network scheduling.

Decision Making Recommendation Systems +1

SE(3) Equivariant Graph Neural Networks with Complete Local Frames

1 code implementation26 Oct 2021 Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Bin Shao, Tie-Yan Liu

In this paper, we propose a framework to construct SE(3) equivariant graph neural networks that can approximate the geometric quantities efficiently.

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD

no code implementations NeurIPS 2021 Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

We prove that with constraint to guarantee low empirical risk, the optimal noise covariance is the square root of the expected gradient covariance if both the prior and the posterior are jointly optimized.

Generalization Bounds

TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks

no code implementations19 Oct 2021 Atul Sharma, Wei Chen, Joshua Zhao, Qiang Qiu, Somali Chaterji, Saurabh Bagchi

The attack uses the intuition that simply by changing the sign of the gradient updates that the optimizer is computing, for a set of malicious clients, a model can be diverted from the optima to increase the test error rate.

Federated Learning Model Poisoning

Does Momentum Change the Implicit Regularization on Separable Data?

no code implementations8 Oct 2021 Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

The momentum acceleration technique is widely adopted in many optimization algorithms.

Regularized-OFU: an efficient algorithm for general contextual bandit with optimization oracles

no code implementations29 Sep 2021 Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu

In contextual bandit, one major challenge is to develop theoretically solid and empirically efficient algorithms for general function classes.

Multi-Armed Bandits Thompson Sampling

Continual Learning with Filter Atom Swapping

1 code implementation ICLR 2022 Zichen Miao, Ze Wang, Wei Chen, Qiang Qiu

In this paper, we first enforce a low-rank filter subspace by decomposing convolutional filters within each network layer over a small set of filter atoms.

Continual Learning

Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback

no code implementations13 Sep 2021 Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang

We study the online influence maximization (OIM) problem in social networks, where the learner repeatedly chooses seed nodes to generate cascades, observes the cascade feedback, and gradually learns the best seeds that generate the largest cascade in multiple rounds.

The Singular Angle of Nonlinear Systems

no code implementations3 Sep 2021 Chao Chen, Wei Chen, Di Zhao, Sei Zhen Khong, Li Qiu

It is, thus, different from the recently appeared nonlinear system phase which adopts the complexification of real-valued signals using the Hilbert transform.

Real-Time Visual Analysis of High-Volume Social Media Posts

no code implementations6 Aug 2021 Johannes Knittel, Steffen Koch, Tan Tang, Wei Chen, Yingcai Wu, Shixia Liu, Thomas Ertl

In contrast to previous work, our system also works with non-geolocated posts and avoids extensive preprocessing such as detecting events.

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit

no code implementations29 Jun 2021 Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu

However, it is in general unknown how to deriveefficient and effective EE trade-off methods for non-linearcomplex tasks, suchas contextual bandit with deep neural network as the reward function.

Multi-Armed Bandits

Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors

no code implementations26 Jun 2021 LiWei Wang, Suraj Yerramilli, Akshay Iyer, Daniel Apley, Ping Zhu, Wei Chen

In addition, an interpretable latent space is obtained to draw insights into the effect of categorical factors, such as those associated with building blocks of architectures and element choices in metamaterial and materials design.

Gaussian Processes Variational Inference

Exploiting Negative Learning for Implicit Pseudo Label Rectification in Source-Free Domain Adaptive Semantic Segmentation

no code implementations23 Jun 2021 Xin Luo, Wei Chen, Yusong Tan, Chen Li, Yulin He, Xiaogang Jia

It is desirable to transfer the knowledge stored in a well-trained source model onto non-annotated target domain in the absence of source data.

Pseudo Label Semantic Segmentation +1

Large Scale Private Learning via Low-rank Reparametrization

1 code implementation17 Jun 2021 Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

We propose a reparametrization scheme to address the challenges of applying differentially private SGD on large neural networks, which are 1) the huge memory cost of storing individual gradients, 2) the added noise suffering notorious dimensional dependence.

Enhanced Hyperspectral Image Super-Resolution via RGB Fusion and TV-TV Minimization

1 code implementation13 Jun 2021 Marija Vella, BoWen Zhang, Wei Chen, João F. C. Mota

Such methods, however, cannot guarantee that the input measurements are satisfied in the recovered image, since the learned parameters by the network are applied to every test image.

Astronomy Hyperspectral Image Super-Resolution +1

Data-Driven Multiscale Design of Cellular Composites with Multiclass Microstructures for Natural Frequency Maximization

no code implementations11 Jun 2021 LiWei Wang, Anton van Beek, Daicong Da, Yu-Chin Chan, Ping Zhu, Wei Chen

After integrating LVGP with the density-based TO, an efficient data-driven cellular composite optimization process is developed to enable concurrent exploration of microstructure concepts and the associated volume fractions for natural frequency optimization.

Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning

no code implementations9 Jun 2021 Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui

For the online learning setting, neither the network structure nor the node weights are known initially.

Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics

no code implementations8 Jun 2021 Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

In this paper, to reduce the reliance on the numerical solver, we propose to enhance the supervised signal in the training of NODE.

Network Inference and Influence Maximization from Samples

no code implementations7 Jun 2021 Zhijie Zhang, Wei Chen, Xiaoming Sun, Jialin Zhang

Our IMS algorithms enhance the learning-and-then-optimization approach by allowing a constant approximation ratio even when the diffusion parameters are hard to learn, and we do not need any assumption related to the network structure or diffusion parameters.

PcDGAN: A Continuous Conditional Diverse Generative Adversarial Network For Inverse Design

1 code implementation7 Jun 2021 Amin Heyrani Nobari, Wei Chen, Faez Ahmed

Engineering design tasks often require synthesizing new designs that meet desired performance requirements.

Design Synthesis Point Processes

Counterfactual Supporting Facts Extraction for Explainable Medical Record Based Diagnosis with Graph Network

1 code implementation NAACL 2021 Haoran Wu, Wei Chen, Shuang Xu, Bo Xu

Specifically, we first structure the sequence of EMR into a hierarchical graph network and then obtain the causal relationship between multi-granularity features and diagnosis results through counterfactual intervention on the graph.

UAV Aided Over-the-Air Computation

no code implementations1 Jun 2021 Min Fu, Yong Zhou, Yuanming Shi, Wei Chen, Rui Zhang

Over-the-air computation (AirComp) seamlessly integrates communication and computation by exploiting the waveform superposition property of multiple-access channels.

Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes

1 code implementation1 Jun 2021 Jian-Wei Zhang, Lei Lv, Yawei Luo, Hao-Zhe Feng, Yi Yang, Wei Chen

The hierarchical features help the model highlight the decision boundary and focus on hard pixels, and the structural information learned from base classes is treated as the prior knowledge for novel classes.

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart

1 code implementation CVPR 2022 Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

Along with this routine, we find that confidence and a rectified confidence (R-Con) can form two coupled rejection metrics, which could provably distinguish wrongly classified inputs from correctly classified ones.

Learning a Model-Driven Variational Network for Deformable Image Registration

no code implementations25 May 2021 Xi Jia, Alexander Thorley, Wei Chen, Huaqi Qiu, Linlin Shen, Iain B Styles, Hyung Jin Chang, Ales Leonardis, Antonio de Marvao, Declan P. O'Regan, Daniel Rueckert, Jinming Duan

We then propose two neural layers (i. e. warping layer and intensity consistency layer) to model the analytical solution and a residual U-Net to formulate the denoising problem (i. e. generalized denoising layer).

Denoising Image Registration

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD

no code implementations NeurIPS 2021 Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

We prove that with constraint to guarantee low empirical risk, the optimal noise covariance is the square root of the expected gradient covariance if both the prior and the posterior are jointly optimized.

Generalization Bounds

CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation

1 code implementation Findings (ACL) 2021 Chujie Zheng, Yong liu, Wei Chen, Yongcai Leng, Minlie Huang

However, existing methods for empathetic response generation usually either consider only one empathy factor or ignore the hierarchical relationships between different factors, leading to a weak ability of empathy modeling.

Empathetic Response Generation Open-Domain Dialog +1

A Graph Neural Network Approach for Product Relationship Prediction

no code implementations12 May 2021 Faez Ahmed, Yaxin Cui, Yan Fu, Wei Chen

By representing products as nodes and their relationships as edges of a graph, we show how an inductive graph neural network approach, named GraphSAGE, can efficiently learn continuous representations for nodes and edges.

Drug Discovery Image Classification +2

Over-the-Air Computation via Reconfigurable Intelligent Surface

no code implementations11 May 2021 Wenzhi Fang, Yuning Jiang, Yuanming Shi, Yong Zhou, Wei Chen, Khaled B. Letaief

Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels.

Geometrical Characterization of Sensor Placement for Cone-Invariant and Multi-Agent Systems against Undetectable Zero-Dynamics Attacks

no code implementations10 May 2021 Jianqi Chen, Jieqiang Wei, Wei Chen, Henrik Sandberg, Karl H. Johansson, Jie Chen

Undetectable attacks are an important class of malicious attacks threatening the security of cyber-physical systems, which can modify a system's state but leave the system output measurements unaffected, and hence cannot be detected from the output.

A Phase Theory of MIMO LTI Systems

no code implementations8 May 2021 Wei Chen, Dan Wang, Sei Zhen Khong, Li Qiu

In this paper, we define the phase response for a class of multi-input multi-output (MIMO) linear time-invariant (LTI) systems whose frequency responses are (semi-)sectorial at all frequencies.

Pure Exploration Bandit Problem with General Reward Functions Depending on Full Distributions

no code implementations8 May 2021 Siwei Wang, Wei Chen

In this paper, we study the pure exploration bandit model on general distribution functions, which means that the reward function of each arm depends on the whole distribution, not only its mean.

Integrating Information Theory and Adversarial Learning for Cross-modal Retrieval

no code implementations11 Apr 2021 Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

Moreover, feature encoders (as a generator) project uni-modal features into a commonly shared space and attempt to fool the discriminator by maximizing its output information entropy.

Cross-Modal Retrieval Retrieval

WNARS: WFST based Non-autoregressive Streaming End-to-End Speech Recognition

no code implementations8 Apr 2021 Zhichao Wang, Wenwen Yang, Pan Zhou, Wei Chen

Recently, attention-based encoder-decoder (AED) end-to-end (E2E) models have drawn more and more attention in the field of automatic speech recognition (ASR).

Automatic Speech Recognition speech-recognition

Delay Analysis of Wireless Federated Learning Based on Saddle Point Approximation and Large Deviation Theory

no code implementations31 Mar 2021 Lintao Li, Longwei Yang, Xin Guo, Yuanming Shi, Haiming Wang, Wei Chen, Khaled B. Letaief

Federated learning (FL) is a collaborative machine learning paradigm, which enables deep learning model training over a large volume of decentralized data residing in mobile devices without accessing clients' private data.

Federated Learning

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders

no code implementations26 Mar 2021 Wei Chen, Kun Zhang, Ruichu Cai, Biwei Huang, Joseph Ramsey, Zhifeng Hao, Clark Glymour

The first step of our method uses the FCI procedure, which allows confounders and is able to produce asymptotically correct results.

Causal Discovery

Lifelong Person Re-Identification via Adaptive Knowledge Accumulation

1 code implementation CVPR 2021 Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

In this work we explore a new and challenging ReID task, namely lifelong person re-identification (LReID), which enables to learn continuously across multiple domains and even generalise on new and unseen domains.

Incremental Learning Person Re-Identification

Magnetoelectric torque and edge currents in spin-orbit coupled graphene nanoribbons

no code implementations12 Mar 2021 Matheus S. M. de Sousa, Manfred Sigrist, Wei Chen

Even without the magnetization, an out-of-plane polarized chiral edge spin current is produced, resembling that in the quantum spin Hall effect.

Mesoscale and Nanoscale Physics

Two Mirroring And Interpolating Methods To Estimate Peak Position For Symmetric Signals With Single Peak

no code implementations12 Mar 2021 Wei Chen

Signals with single peak and symmetry property are very common in various fields, such as probability density function of normal distribution.

PREPRINT: Comparison of deep learning and hand crafted features for mining simulation data

no code implementations11 Mar 2021 Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck, Nan Pu, Wei Chen, Michael Lew

The output of such simulations, in particular the calculated flow fields, are usually very complex and hard to interpret for realistic three-dimensional real-world applications, especially if time-dependent simulations are investigated.

A Sequential Variational Mode Decomposition Method

no code implementations10 Mar 2021 Wei Chen

And in such a way, the mode number also can be determined during the separation procedure.

Range-GAN: Range-Constrained Generative Adversarial Network for Conditioned Design Synthesis

1 code implementation10 Mar 2021 Amin Heyrani Nobari, Wei Chen, Faez Ahmed

This work laid the foundation for data-driven inverse design problems where we consider range constraints and there are sparse regions in the condition space.

3D Shape Generation Design Synthesis

A Note on the Boundedness of Doob Maximal Operators on a Filtered Measure Space

no code implementations4 Mar 2021 Wei Chen, Jingya Cui

Let $M$ be the Doob maximal operator on a filtered measure space and let $v$ be an $A_p$ weight with $1<p<+\infty$.

Probability 60G46

Realizing Majorana fermion modes in the Kitaev model

no code implementations4 Mar 2021 Jia-Xing Zhang, Lu Yang, Shuang Liang, Wei Chen, Qiang-Hua Wang

We study the possibility to realize Majorana zero mode that's robust and may be easily manipulated for braiding in quantum computing in the ground state of the Kitaev model in this work.

Strongly Correlated Electrons

Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning

2 code implementations ICLR 2021 Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu

The privacy leakage of the model about the training data can be bounded in the differential privacy mechanism.

Combinatorial Pure Exploration with Bottleneck Reward Function

no code implementations NeurIPS 2021 Yihan Du, Yuko Kuroki, Wei Chen

For the FC setting, we propose novel algorithms with optimal sample complexity for a broad family of instances and establish a matching lower bound to demonstrate the optimality (within a logarithmic factor).

Aharonov-Bohm Effect in Three-dimensional Higher-order Topological Insulator

no code implementations28 Jan 2021 Kun Luo, Hao Geng, Li Sheng, Wei Chen, D. Y. Xing

Unlike AB interferometer of 3D topological insulator(TI), we find that there are different AB oscillation frequencies for a given direction of magnetic field in 3D HOTI.

Mesoscale and Nanoscale Physics

Deep Learning for Instance Retrieval: A Survey

no code implementations27 Jan 2021 Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew

In recent years a vast amount of visual content has been generated and shared from many fields, such as social media platforms, medical imaging, and robotics.

Content-Based Image Retrieval Instance Search +1

UAV-Assisted Over-the-Air Computation

no code implementations25 Jan 2021 Min Fu, Yong Zhou, Yuanming Shi, Ting Wang, Wei Chen

Over-the-air computation (AirComp) provides a promising way to support ultrafast aggregation of distributed data.

Optimize the trajectory of UAV which plays a BS in communication system

Search for the elusive jet-induced diffusion wake in $Z/γ$-jets with 2D jet tomography in high-energy heavy-ion collisions

no code implementations14 Jan 2021 Zhong Yang, Wei Chen, Yayun He, Weiyao Ke, Longgang Pang, Xin-Nian Wang

Diffusion wake is an unambiguous part of the jet-induced medium response in high-energy heavy-ion collisions that leads to a depletion of soft hadrons in the opposite direction of the jet propagation.

High Energy Physics - Phenomenology

BN-invariant sharpness regularizes the training model to better generalization

no code implementations8 Jan 2021 Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

However, it has been pointed out that the usual definitions of sharpness, which consider either the maxima or the integral of loss over a $\delta$ ball of parameters around minima, cannot give consistent measurement for scale invariant neural networks, e. g., networks with batch normalization layer.

Deep Generative Model for Efficient 3D Airfoil Parameterization and Generation

no code implementations7 Jan 2021 Wei Chen, Arun Ramamurthy

We demonstrate FFD-GAN's performance using a wing shape design example.

On the Stability of Multi-branch Network

no code implementations1 Jan 2021 Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu

More importantly, we propose a new design ``STAM aggregation" that can guarantee to STAbilize the forward/backward process of Multi-branch networks irrespective of the number of branches.

FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine Translation

1 code implementation LREC 2022 Wenhao Zhu, ShuJian Huang, Tong Pu, Pingxuan Huang, Xu Zhang, Jian Yu, Wei Chen, Yanfeng Wang, Jiajun Chen

Previous research for adapting a general neural machine translation (NMT) model into a specific domain usually neglects the diversity in translation within the same domain, which is a core problem for domain adaptation in real-world scenarios.

Autonomous Vehicles Domain Adaptation +3

A Plug-and-Play Priors Framework for Hyperspectral Unmixing

1 code implementation24 Dec 2020 Min Zhao, Xiuheng Wang, Jie Chen, Wei Chen

Spectral unmixing is a widely used technique in hyperspectral image processing and analysis.

Hyperspectral Unmixing Image Denoising

Time Series Domain Adaptation via Sparse Associative Structure Alignment

no code implementations22 Dec 2020 Ruichu Cai, Jiawei Chen, Zijian Li, Wei Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang

To reduce the difficulty in the discovery of causal structure, we relax it to the sparse associative structure and propose a novel sparse associative structure alignment model for domain adaptation.

Domain Adaptation Time Series

Identifying Invariant Texture Violation for Robust Deepfake Detection

no code implementations19 Dec 2020 Xinwei Sun, Botong Wu, Wei Chen

To learn such an invariance for deepfake detection, our InTeLe introduces an auto-encoder framework with different decoders for pristine and fake images, which are further appended with a shallow classifier in order to separate out the obvious artifact-effect.

DeepFake Detection Face Swapping

The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks

1 code implementation11 Dec 2020 Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu

Except GD, adaptive algorithms such as AdaGrad, RMSProp and Adam are popular owing to their rapid training process.

Multitask machine learning of collective variables for enhanced sampling of rare events

no code implementations7 Dec 2020 Lixin Sun, Jonathan Vandermause, Simon Batzner, Yu Xie, David Clark, Wei Chen, Boris Kozinsky

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics.

BIG-bench Machine Learning Dimensionality Reduction

Phase of Nonlinear Systems

no code implementations30 Nov 2020 Chao Chen, Di Zhao, Wei Chen, Sei Zhen Khong, Li Qiu

A nonlinear small phase theorem is then established for feedback stability analysis of semi-sectorial systems.

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

3 code implementations21 Nov 2020 Hao-Zhe Feng, Kezhi Kong, Minghao Chen, Tianye Zhang, Minfeng Zhu, Wei Chen

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference results.

Semi-Supervised Image Classification Variational Inference

A universal simulating framework for quantum key distribution systems

no code implementations17 Nov 2020 Guan-Jie Fan-Yuan, Wei Chen, Feng-Yu Lu, Zhen-Qiang Yin, Shuang Wang, Guang-Can Guo, Zheng-Fu Han

Our framework focuses on realistic characters of optical devices and system structures.

Quantum Physics Optics

Online Influence Maximization under Linear Threshold Model

no code implementations NeurIPS 2020 Shuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen

Based on the linear structure in node activations, we incorporate ideas from linear bandits and design an algorithm LT-LinUCB that is consistent with the observed feedback.

Federated Learning via Intelligent Reflecting Surface

no code implementations10 Nov 2020 Zhibin Wang, Jiahang Qiu, Yong Zhou, Yuanming Shi, Liqun Fu, Wei Chen, Khaled B. Lataief

To optimize the learning performance, we formulate an optimization problem that jointly optimizes the device selection, the aggregation beamformer at the base station (BS), and the phase shifts at the IRS to maximize the number of devices participating in the model aggregation of each communication round under certain mean-squared-error (MSE) requirements.

Federated Learning

Enhanced Few-shot Learning for Intrusion Detection in Railway Video Surveillance

no code implementations9 Nov 2020 Xiao Gong, Xi Chen, Wei Chen

Video surveillance is gaining increasing popularity to assist in railway intrusion detection in recent years.

Few-Shot Learning Intrusion Detection

Latent Causal Invariant Model

no code implementations4 Nov 2020 Xinwei Sun, Botong Wu, Xiangyu Zheng, Chang Liu, Wei Chen, Tao Qin, Tie-Yan Liu

To avoid spurious correlation, we propose a Latent Causal Invariance Model (LaCIM) which pursues causal prediction.

Disentanglement

Learning Causal Semantic Representation for Out-of-Distribution Prediction

1 code implementation NeurIPS 2021 Chang Liu, Xinwei Sun, Jindong Wang, Haoyue Tang, Tao Li, Tao Qin, Wei Chen, Tie-Yan Liu

Conventional supervised learning methods, especially deep ones, are found to be sensitive to out-of-distribution (OOD) examples, largely because the learned representation mixes the semantic factor with the variation factor due to their domain-specific correlation, while only the semantic factor causes the output.

Domain Adaptation

Establishing the first hidden-charm pentaquark with strangeness

no code implementations2 Nov 2020 Hua-Xing Chen, Wei Chen, Xiang Liu, Xiao-Hai Liu

We study the $P_{cs}(4459)^0$ recently observed by LHCb using the method of QCD sum rules.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Fast Convergence Algorithm for Analog Federated Learning

no code implementations30 Oct 2020 Shuhao Xia, Jingyang Zhu, Yuhan Yang, Yong Zhou, Yuanming Shi, Wei Chen

In this paper, we consider federated learning (FL) over a noisy fading multiple access channel (MAC), where an edge server aggregates the local models transmitted by multiple end devices through over-the-air computation (AirComp).

Federated Learning

Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth

no code implementations29 Oct 2020 Wei Chen, BoWen Zhang, Shi Jin, Bo Ai, Zhangdui Zhong

Sparse signal recovery problems from noisy linear measurements appear in many areas of wireless communications.

New Ideas and Trends in Deep Multimodal Content Understanding: A Review

no code implementations16 Oct 2020 Wei Chen, Weiping Wang, Li Liu, Michael S. Lew

The focus of this survey is on the analysis of two modalities of multimodal deep learning: image and text.

Cross-Modal Retrieval Image Captioning +5

On the Exploration of Incremental Learning for Fine-grained Image Retrieval

1 code implementation15 Oct 2020 Wei Chen, Yu Liu, Weiping Wang, Tinne Tuytelaars, Erwin M. Bakker, Michael Lew

On the other hand, fine-tuning the learned representation only with the new classes leads to catastrophic forgetting.

Image Retrieval Incremental Learning +1

Hyperspectral Unmixing via Nonnegative Matrix Factorization with Handcrafted and Learnt Priors

no code implementations9 Oct 2020 Min Zhao, Tiande Gao, Jie Chen, Wei Chen

In our work, we propose an NMF based unmixing framework which jointly uses a handcrafting regularizer and a learnt regularizer from data.

Hyperspectral Unmixing

Fully Automatic Intervertebral Disc Segmentation Using Multimodal 3D U-Net

no code implementations28 Sep 2020 Chuanbo Wang, Ye Guo, Wei Chen, Zeyun Yu

With the advance of deep learning, various neural network models have gained great success in image analysis including the recognition of intervertebral discs.

ChoreoNet: Towards Music to Dance Synthesis with Choreographic Action Unit

no code implementations16 Sep 2020 Zijie Ye, Haozhe Wu, Jia Jia, Yaohua Bu, Wei Chen, Fanbo Meng, Yan-Feng Wang

Meanwhile, human choreographers design dance motions from music in a two-stage manner: they firstly devise multiple choreographic dance units (CAUs), each with a series of dance motions, and then arrange the CAU sequence according to the rhythm, melody and emotion of the music.

MO-PaDGAN: Reparameterizing Engineering Designs for Augmented Multi-objective Optimization

1 code implementation15 Sep 2020 Wei Chen, Faez Ahmed

Despite their success in capturing complex distributions, existing generative models face three challenges when used for design problems: 1) generated designs have limited design space coverage, 2) the generator ignores design performance, and 3)~the new parameterization is unable to represent designs beyond training data.

Point Processes

GraphFederator: Federated Visual Analysis for Multi-party Graphs

no code implementations27 Aug 2020 Dongming Han, Wei Chen, Rusheng Pan, Yijing Liu, Jiehui Zhou, Ying Xu, Tianye Zhang, Changjie Fan, Jianrong Tao, Xiaolong, Zhang

This paper presents GraphFederator, a novel approach to construct joint representations of multi-party graphs and supports privacy-preserving visual analysis of graphs.

Human-Computer Interaction Cryptography and Security Graphics

New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design

no code implementations25 Aug 2020 Kartikeya Bhardwaj, Wei Chen, Radu Marculescu

In this paper, we first highlight three major challenges to large-scale adoption of deep learning at the edge: (i) Hardware-constrained IoT devices, (ii) Data security and privacy in the IoT era, and (iii) Lack of network-aware deep learning algorithms for distributed inference across multiple IoT devices.

Federated Learning

Global Context Aware Convolutions for 3D Point Cloud Understanding

no code implementations7 Aug 2020 Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung

We found that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive.

Point Cloud Classification Retrieval +1

Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification

1 code implementation6 Aug 2020 Nan Pu, Wei Chen, Yu Liu, Erwin M. Bakker, Michael S. Lew

To solve the problem, we present a carefully designed dual Gaussian-based variational auto-encoder (DG-VAE), which disentangles an identity-discriminable and an identity-ambiguous cross-modality feature subspace, following a mixture-of-Gaussians (MoG) prior and a standard Gaussian distribution prior, respectively.

Disentanglement Person Re-Identification +2

SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization

no code implementations30 Jul 2020 Jiazhi Xia, Tianxiang Chen, Lei Zhang, Wei Chen, Yang Chen, Xiaolong Zhang, Cong Xie, Tobias Schreck

We build a prototype system based on our method, SMAP, to support the organization, computation, and exploration of secure joint embedding.

Dimensionality Reduction

Revisiting the Modifiable Areal Unit Problem in Deep Traffic Prediction with Visual Analytics

no code implementations30 Jul 2020 Wei Zeng, Chengqiao Lin, Juncong Lin, Jincheng Jiang, Jiazhi Xia, Cagatay Turkay, Wei Chen

Deep learning methods are being increasingly used for urban traffic prediction where spatiotemporal traffic data is aggregated into sequentially organized matrices that are then fed into convolution-based residual neural networks.

Association Traffic Prediction

Deep Learning Methods for Solving Linear Inverse Problems: Research Directions and Paradigms

no code implementations27 Jul 2020 Yanna Bai, Wei Chen, Jie Chen, Weisi Guo

The linear inverse problem is fundamental to the development of various scientific areas.

How Does Data Augmentation Affect Privacy in Machine Learning?

1 code implementation21 Jul 2020 Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu

Even further, we show that the proposed approach can achieve higher MI attack success rates on models trained with some data augmentation than the existing methods on models trained without data augmentation.

BIG-bench Machine Learning Data Augmentation

MO-PaDGAN: Generating Diverse Designs with Multivariate Performance Enhancement

no code implementations7 Jul 2020 Wei Chen, Faez Ahmed

Deep generative models have proven useful for automatic design synthesis and design space exploration.

Design Synthesis Point Processes

Optimization from Structured Samples for Coverage Functions

no code implementations ICML 2020 Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang

We revisit the optimization from samples (OPS) model, which studies the problem of optimizing objective functions directly from the sample data.

Molecular Latent Space Simulators

no code implementations1 Jul 2020 Hythem Sidky, Wei Chen, Andrew L. Ferguson

Small integration time steps limit molecular dynamics (MD) simulations to millisecond time scales.

Robust Neural Machine Translation with ASR Errors

no code implementations WS 2020 Haiyang Xue, Yang Feng, Shuhao Gu, Wei Chen

In this paper, we propose a method to handle the two problems so as to generate robust translation to ASR errors.

Automatic Speech Recognition Machine Translation +2

Data-Driven Topology Optimization with Multiclass Microstructures using Latent Variable Gaussian Process

no code implementations27 Jun 2020 Liwei Wang, Siyu Tao, Ping Zhu, Wei Chen

With this model, we can easily obtain a continuous and differentiable transition between different microstructure concepts that can render gradient information for multiscale topology optimization.

Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems

no code implementations27 Jun 2020 Liwei Wang, Yu-Chin Chan, Faez Ahmed, Zhao Liu, Ping Zhu, Wei Chen

For microstructure design, the tuning of mechanical properties and complex manipulations of microstructures are easily achieved by simple vector operations in the latent space.

Dynamic of Stochastic Gradient Descent with State-Dependent Noise

no code implementations24 Jun 2020 Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Specifically, we show that the covariance of the noise of SGD in the local region of the local minima is a quadratic function of the state.

Online Competitive Influence Maximization

no code implementations24 Jun 2020 Jinhang Zuo, Xutong Liu, Carlee Joe-Wong, John C. S. Lui, Wei Chen

In this paper, we introduce a new Online Competitive Influence Maximization (OCIM) problem, where two competing items (e. g., products, news stories) propagate in the same network and influence probabilities on edges are unknown.

Combinatorial Pure Exploration of Dueling Bandit

no code implementations23 Jun 2020 Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao

For Borda winner, we establish a reduction of the problem to the original CPE-MAB setting and design PAC and exact algorithms that achieve both the sample complexity similar to that in the CPE-MAB setting (which is nearly optimal for a subclass of problems) and polynomial running time per round.

Airfoil Design Parameterization and Optimization using Bézier Generative Adversarial Networks

1 code implementation21 Jun 2020 Wei Chen, Kevin Chiu, Mark Fuge

The resulted new parameterization can accelerate design optimization convergence by improving the representation compactness while maintaining sufficient representation capacity.

Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback

no code implementations14 Jun 2020 Yihan Du, Yuko Kuroki, Wei Chen

In this paper, we first study the problem of combinatorial pure exploration with full-bandit feedback (CPE-BL), where a learner is given a combinatorial action space $\mathcal{X} \subseteq \{0, 1\}^d$, and in each round the learner pulls an action $x \in \mathcal{X}$ and receives a random reward with expectation $x^{\top} \theta$, with $\theta \in \mathbb{R}^d$ a latent and unknown environment vector.

Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference

no code implementations4 Jun 2020 Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang

Modern deep neural networks increasingly make use of features such as dynamic control flow, data structures and dynamic tensor shapes.

(Locally) Differentially Private Combinatorial Semi-Bandits

no code implementations ICML 2020 Xiaoyu Chen, Kai Zheng, Zixin Zhou, Yunchang Yang, Wei Chen, Li-Wei Wang

In this paper, we study Combinatorial Semi-Bandits (CSB) that is an extension of classic Multi-Armed Bandits (MAB) under Differential Privacy (DP) and stronger Local Differential Privacy (LDP) setting.

Multi-Armed Bandits Privacy Preserving

METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design

1 code implementation1 Jun 2020 Yu-Chin Chan, Faez Ahmed, Li-Wei Wang, Wei Chen

In answer, we posit that a smaller yet diverse set of unit cells leads to scalable search and unbiased learning.

Physical Simulations Point Processes

Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech

8 code implementations Interspeech2020 2020 Geng Yang, Shan Yang, Kai Liu, Peng Fang, Wei Chen, Lei Xie

In this paper, we propose multi-band MelGAN, a much faster waveform generation model targeting to high-quality text-to-speech.

Sound Audio and Speech Processing

Quda: Natural Language Queries for Visual Data Analytics

no code implementations7 May 2020 Siwei Fu, Kai Xiong, Xiaodong Ge, Siliang Tang, Wei Chen, Yingcai Wu

To address this challenge, we present a new dataset, called Quda, that aims to help V-NLIs recognize analytic tasks from free-form natural language by training and evaluating cutting-edge multi-label classification models.

Multi-Label Classification Natural Language Queries +1

EnsembleGAN: Adversarial Learning for Retrieval-Generation Ensemble Model on Short-Text Conversation

no code implementations30 Apr 2020 Jiayi Zhang, Chongyang Tao, Zhenjing Xu, Qiaojing Xie, Wei Chen, Rui Yan

Aiming at generating responses that approximate the ground-truth and receive high ranking scores from the discriminator, the two generators learn to generate improved highly relevant responses and competitive unobserved candidates respectively, while the discriminative ranker is trained to identify true responses from adversarial ones, thus featuring the merits of both generator counterparts.

Language Modelling Retrieval +1