Search Results for author: Wei Chen

Found 220 papers, 45 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.

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

Online Influence Maximization with Node-level Feedback Using Standard Offline Oracles

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

So we focus on how to use the standard offline influence maximization oracle which finds the best seed set given the edge parameters as input.

End-to-End Conversational Search for Online Shopping with Utterance Transfer

no code implementations12 Sep 2021 Liqiang Xiao, Jun Ma2, Xin Luna Dong, Pascual Martinez-Gomez, Nasser Zalmout, Wei Chen, Tong Zhao, Hao He, Yaohui Jin

Successful conversational search systems can present natural, adaptive and interactive shopping experience for online shopping customers.

Conversational Search

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.

Causally Invariant Predictor with Shift-Robustness

no code implementations5 Jul 2021 Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu

Instead of imposing regularizations to constrain the invariance of the predictor, we propose to predict by the intervened conditional expectation based on the do-operator and then prove that it is invariant across domains.

Causal Discovery

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.

Domain Adaptation Rectification +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.

Hyperspectral Image Super-Resolution Image Super-Resolution

PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Driven Adaptive Prior

no code implementations11 Jun 2021 Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu

Denoising diffusion probabilistic models have been recently proposed to generate high-quality samples by estimating the gradient of the data density.


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

Specifically, beyond learning directly from the trajectory samples, we pre-train a neural differential operator (NDO) to output an estimation of the derivatives to serve as an additional supervised signal.

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

Network Inference and Influence Maximization from Samples

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

We study the task of influence maximization from these cascade samples (IMS), and present constant approximation algorithms for this task under mild conditions on the seed set distribution.

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

no code implementations 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.

Adversarial Training with Rectified Rejection

1 code implementation31 May 2021 Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu

Adversarial training (AT) is one of the most effective strategies for promoting model robustness, whereas even the state-of-the-art adversarially trained models struggle to exceed 60% robust test accuracy on CIFAR-10 without additional data, which is far from practical.

Machine-Learning Non-Conservative Dynamics for New-Physics Detection

no code implementations31 May 2021 Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu

Energy conservation is a basic physics principle, the breakdown of which often implies new physics.

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

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

1 code implementation18 May 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.

Open-Domain Dialog

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 introduce a definition of 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

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 End-To-End Speech Recognition +1

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.

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 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.

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

no code implementations4 Mar 2021 Wei Chen, Jingya Cui

However, we show that $$\lim\limits_{p\rightarrow+\infty}p^{\frac{1}{p-1}}=\lim\limits_{p\rightarrow+\infty}(\min\limits_{a>1}a^{\frac{2}{p}}\eta^{(p^{\prime}-1)})=1.$$

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 show that in both cases, the system binds a vortex with the defect and a robust Majorana zero mode in the ground state at a weak uniform conical magnetic field.

Strongly Correlated Electrons

IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures

no code implementations3 Mar 2021 Jun Wang, Wei Chen, Mark Fuge, Rahul Rai

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically-optimized, functionally graded structures, particularly when those structures are represented as discrete density maps.

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

1 code implementation 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 and its Extension to General Reward Functions

no code implementations24 Feb 2021 Yihan Du, Yuko Kuroki, Wei Chen

In this paper, we study the Combinatorial Pure Exploration problem with the bottleneck reward function (CPE-B) under the fixed-confidence and fixed-budget settings.

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 Image 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

More specifically, we focus on image retrieval with deep learning and organize the state of the art methods according to the types of deep network structure, deep features, feature enhancement methods, and network fine-tuning strategies.

Content-Based Image Retrieval

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.

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

Towards Accelerating Training of Batch Normalization: A Manifold Perspective

no code implementations8 Jan 2021 Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma

Then, gradient descent and stochastic gradient descent on the PSI manifold are also constructed.

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.

FDMT: A Benchmark Dataset for Fine-grained Domain Adaptation in Machine Translation

no code implementations31 Dec 2020 Wenhao Zhu, ShuJian Huang, Tong Pu, Xu Zhang, Jian Yu, Wei Chen, Yanfeng Wang, Jiajun Chen

To motivate a wide investigation in such settings, we present a real-world fine-grained domain adaptation task in machine translation (FDMT).

Autonomous Vehicles Domain Adaptation +1

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.

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.

Learning Causal Semantic Representation for Out-of-Distribution Prediction

no code implementations3 Nov 2020 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 +4

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

no code implementations15 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

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 Scene Understanding

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.

Person Re-Identification Variational Inference

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.

Traffic Prediction

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

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.

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.

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 +1

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.

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

We provide a nontrivial proof showing that the Triggering Probability Modulated (TPM) condition for CMAB still holds in OCIM, which is instrumental for our proposed algorithms OCIM-TS and OCIM-OFU to achieve logarithmic Bayesian regret and frequentist regret, respectively.

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.

Global Optimization

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.

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

(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

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

5 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 Paraphrase Generation

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 Short-Text Conversation

Lightweight Mask R-CNN for Long-Range Wireless Power Transfer Systems

no code implementations19 Apr 2020 Hao Li, Aozhou Wu, Wen Fang, Qingqing Zhang, Mingqing Liu, Qingwen Liu, Wei Chen

The proposed approach makes the object detection much easier to be transplanted on mobile devices and reduce the burden of hardware computation.

Object Detection

Efficient Approximation Algorithms for Adaptive Influence Maximization

2 code implementations14 Apr 2020 Keke Huang, Jing Tang, Kai Han, Xiaokui Xiao, Wei Chen, Aixin Sun, Xueyan Tang, Andrew Lim

In this paper, we propose the first practical algorithm for the adaptive IM problem that could provide the worst-case approximation guarantee of $1-\mathrm{e}^{\rho_b(\varepsilon-1)}$, where $\rho_b=1-(1-1/b)^b$ and $\varepsilon \in (0, 1)$ is a user-specified parameter.

Social and Information Networks

Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface

no code implementations13 Apr 2020 Kai Yang, Yuanming Shi, Yong Zhou, Zhanpeng Yang, Liqun Fu, Wei Chen

Intelligent Internet-of-Things (IoT) will be transformative with the advancement of artificial intelligence and high-dimensional data analysis, shifting from "connected things" to "connected intelligence".

Self-Driving Cars

MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning

1 code implementation8 Apr 2020 Nannapas Banluesombatkul, Pichayoot Ouppaphan, Pitshaporn Leelaarporn, Payongkit Lakhan, Busarakum Chaitusaney, Nattapong Jaimchariyatam, Ekapol Chuangsuwanich, Wei Chen, Huy Phan, Nat Dilokthanakul, Theerawit Wilaiprasitporn

This is the first work that investigated a non-conventional pre-training method, MAML, resulting in a possibility for human-machine collaboration in sleep stage classification and easing the burden of the clinicians in labelling the sleep stages through only several epochs rather than an entire recording.

Automatic Sleep Stage Classification Meta-Learning +1

FedMAX: Mitigating Activation Divergence for Accurate and Communication-Efficient Federated Learning

1 code implementation7 Apr 2020 Wei Chen, Kartikeya Bhardwaj, Radu Marculescu

In this paper, we identify a new phenomenon called activation-divergence which occurs in Federated Learning (FL) due to data heterogeneity (i. e., data being non-IID) across multiple users.

Federated Learning

Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation

no code implementations30 Mar 2020 Pei Zhang, Xu Zhang, Wei Chen, Jian Yu, Yan-Feng Wang, Deyi Xiong

In this paper, we propose a new framework to model cross-sentence dependencies by training neural machine translation (NMT) to predict both the target translation and surrounding sentences of a source sentence.

Document-level Document Level Machine Translation +2

G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features

1 code implementation CVPR 2020 Wei Chen, Xi Jia, Hyung Jin Chang, Jinming Duan, Ales Leonardis

Third, via the predicted segmentation and translation, we transfer the fine object point cloud into a local canonical coordinate, in which we train a rotation localization network to estimate initial object rotation.

6D Pose Estimation 6D Pose Estimation using RGB

PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs

1 code implementation26 Feb 2020 Wei Chen, Faez Ahmed

With this new loss function, we develop a variant of the Generative Adversarial Network, named "Performance Augmented Diverse Generative Adversarial Network" or PaDGAN, which can generate novel high-quality designs with good coverage of the design space.

Design Synthesis Point Processes

Combinatorial Semi-Bandit in the Non-Stationary Environment

no code implementations10 Feb 2020 Wei Chen, Li-Wei Wang, Haoyu Zhao, Kai Zheng

In a special case where the reward function is linear and we have an exact oracle, we design a parameter-free algorithm that achieves nearly optimal regret both in the switching case and in the dynamic case without knowing the parameters in advance.

Gradient Perturbation is Underrated for Differentially Private Convex Optimization

no code implementations26 Nov 2019 Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin

By using the \emph{expected curvature}, we show that gradient perturbation can achieve a significantly improved utility guarantee that can theoretically justify the advantage of gradient perturbation over other perturbation methods.

Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization

no code implementations19 Nov 2019 Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao

On the other side, we prove that in any submodular cascade, the adaptive greedy algorithm always outputs a $(1-1/e)$-approximation to the expected number of adoptions in the optimal non-adaptive seed choice.

Social and Information Networks

Online Second Price Auction with Semi-bandit Feedback Under the Non-Stationary Setting

no code implementations14 Nov 2019 Haoyu Zhao, Wei Chen

The problem is more challenging than the standard online learning scenario since the private value distribution is non-stationary, meaning that the distribution of bidders' private values may change over time, and we need to use the \emph{non-stationary regret} to measure the performance of our algorithm.

Interpreting Basis Path Set in Neural Networks

no code implementations18 Oct 2019 Juanping Zhu, Qi Meng, Wei Chen, Zhi-Ming Ma

Based on basis path set, G-SGD algorithm significantly outperforms conventional SGD algorithm in optimizing neural networks.

A Conditional Generative Model for Predicting Material Microstructures from Processing Methods

no code implementations4 Oct 2019 Akshay Iyer, Biswadip Dey, Arindam Dasgupta, Wei Chen, Amit Chakraborty

Microstructures of a material form the bridge linking processing conditions - which can be controlled, to the material property - which is the primary interest in engineering applications.

Feature Engineering Image Generation

Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables

no code implementations3 Oct 2019 Yichi Zhang, Daniel Apley, Wei Chen

We present in this paper the integration of a novel latent-variable (LV) approach for mixed-variable GP modeling with the BO framework for materials design.

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design

no code implementations4 Jul 2019 Akshay Iyer, Yichi Zhang, Aditya Prasad, Siyu Tao, Yixing Wang, Linda Schadler, L Catherine Brinson, Wei Chen

To this end, we present a data-centric, mixed-variable Bayesian Optimization framework that integrates data from literature, experiments, and simulations for knowledge discovery and computational materials design.

On Adaptivity Gaps of Influence Maximization under the Independent Cascade Model with Full Adoption Feedback

no code implementations3 Jul 2019 Wei Chen, Binghui Peng

In this paper, we study the adaptivity gap of the influence maximization problem under independent cascade model when full-adoption feedback is available.

Social and Information Networks

Stochastic One-Sided Full-Information Bandit

no code implementations20 Jun 2019 Haoyu Zhao, Wei Chen

In this paper, we study the stochastic version of the one-sided full information bandit problem, where we have $K$ arms $[K] = \{1, 2, \ldots, K\}$, and playing arm $i$ would gain reward from an unknown distribution for arm $i$ while obtaining reward feedback for all arms $j \ge i$.

High-resolution Markov state models for the dynamics of Trp-cage miniprotein constructed over slow folding modes identified by state-free reversible VAMPnets

no code implementations12 Jun 2019 Hythem Sidky, Wei Chen, Andrew L. Ferguson

State-free reversible VAMPnets (SRVs) are a neural network-based framework capable of learning the leading eigenfunctions of the transfer operator of a dynamical system from trajectory data.

Factorization Bandits for Online Influence Maximization

1 code implementation9 Jun 2019 Qingyun Wu, Zhige Li, Huazheng Wang, Wei Chen, Hongning Wang

We capitalize on an important property of the influence maximization problem named network assortativity, which is ignored by most existing works in online influence maximization.

Self-Activation Influence Maximization

no code implementations5 Jun 2019 Lichao Sun, Albert Chen, Philip S. Yu, Wei Chen

We incorporate self activation into influence propagation and propose the self-activation independent cascade (SAIC) model: nodes may be self activated besides being selected as seeds, and influence propagates from both selected seeds and self activated nodes.

Social and Information Networks

Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems

no code implementations2 Jun 2019 Wei Chen, Hythem Sidky, Andrew L. Ferguson

We also compare the TAE results with those obtained using state-free reversible VAMPnets (SRVs) as a variational-based neural network approach for slow modes discovery, and show that SRVs can correctly discover slow modes where TAEs fail.

Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data

no code implementations29 May 2019 Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu

Our theory captures how the convergence of distributed algorithms behaves as the number of machines and the size of local data vary.

Adaptive Influence Maximization with Myopic Feedback

no code implementations NeurIPS 2019 Binghui Peng, Wei Chen

We study the adaptive influence maximization problem with myopic feedback under the independent cascade model: one sequentially selects k nodes as seeds one by one from a social network, and each selected seed returns the immediate neighbors it activates as the feedback available for later selections, and the goal is to maximize the expected number of total activated nodes, referred as the influence spread.

Social and Information Networks

An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE

no code implementations22 May 2019 Tianye Zhang, Haozhe Feng, Zexian Chen, Can Wang, Yanhao Huang, Yong Tang, Wei Chen

Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid.

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space

no code implementations ICLR 2019 Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Then, a natural question is: \emph{can we construct a new vector space that is positively scale-invariant and sufficient to represent ReLU neural networks so as to better facilitate the optimization process }?

Optimization on Multiple Manifolds

no code implementations ICLR 2019 Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Optimization on manifold has been widely used in machine learning, to handle optimization problems with constraint.

The Roadmap to 6G -- AI Empowered Wireless Networks

no code implementations26 Apr 2019 Khaled B. Letaief, Wei Chen, Yuanming Shi, Jun Zhang, Ying-Jun Angela Zhang

The recent upsurge of diversified mobile applications, especially those supported by Artificial Intelligence (AI), is spurring heated discussions on the future evolution of wireless communications.

DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis

3 code implementations CVPR 2019 Minfeng Zhu, Pingbo Pan, Wei Chen, Yi Yang

If the initial image is not well initialized, the following processes can hardly refine the image to a satisfactory quality.

Ranked #2 on Text-to-Image Generation on COCO (SOA-C metric)

Text-to-Image Generation

Convergence Theory of Learning Over-parameterized ResNet: A Full Characterization

1 code implementation17 Mar 2019 Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu

Specifically, with hiding logarithmic factor and constant coefficients, we show that for $\tau\le 1/\sqrt{L}$ gradient descent is guaranteed to converge to the global minma, and especially when $\tau\le 1/L$ the convergence is irrelevant of the network depth.

Reinforcement Learning with Dynamic Boltzmann Softmax Updates

1 code implementation14 Mar 2019 Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, Tie-Yan Liu

In this paper, we propose to update the value function with dynamic Boltzmann softmax (DBS) operator, which has good convergence property in the setting of planning and learning.

Atari Games Q-Learning

Positively Scale-Invariant Flatness of ReLU Neural Networks

no code implementations6 Mar 2019 Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

That is to say, the minimum with balanced values of basis paths will more likely to be flatter and generalize better.

Stochastic Online Learning with Probabilistic Graph Feedback

no code implementations4 Mar 2019 Shuai Li, Wei Chen, Zheng Wen, Kwong-Sak Leung

We consider a problem of stochastic online learning with general probabilistic graph feedback, where each directed edge in the feedback graph has probability $p_{ij}$.

Improved Algorithm on Online Clustering of Bandits

no code implementations25 Feb 2019 Wei Chen, Shuai Li, Kwong-Sak Leung

We generalize the setting of online clustering of bandits by allowing non-uniform distribution over user frequencies.

Online Clustering

Nonlinear Discovery of Slow Molecular Modes using State-Free Reversible VAMPnets

no code implementations9 Feb 2019 Wei Chen, Hythem Sidky, Andrew L. Ferguson

The success of enhanced sampling molecular simulations that accelerate along collective variables (CVs) is predicated on the availability of variables coincident with the slow collective motions governing the long-time conformational dynamics of a system.

Vector and Line Quantization for Billion-scale Similarity Search on GPUs

1 code implementation2 Jan 2019 Wei Chen, Jincai Chen, Fuhao Zou, Yuan-Fang Li, Ping Lu, Qiang Wang, Wei Zhao

The inverted index structure is amenable to GPU-based implementations, and the state-of-the-art systems such as Faiss are able to exploit the massive parallelism offered by GPUs.


On the Local Hessian in Back-propagation

no code implementations NeurIPS 2018 Huishuai Zhang, Wei Chen, Tie-Yan Liu

We study the Hessian of the local back-matching loss (local Hessian) and connect it to the efficiency of BP.

Learning to Predict the Cosmological Structure Formation

1 code implementation15 Nov 2018 Siyu He, Yin Li, Yu Feng, Shirley Ho, Siamak Ravanbakhsh, Wei Chen, Barnabás Póczos

We build a deep neural network, the Deep Density Displacement Model (hereafter D$^3$M), to predict the non-linear structure formation of the Universe from simple linear perturbation theory.

Community Exploration: From Offline Optimization to Online Learning

no code implementations NeurIPS 2018 Xiaowei Chen, Weiran Huang, Wei Chen, John C. S. Lui

We introduce the community exploration problem that has many real-world applications such as online advertising.

Exploring RNN-Transducer for Chinese Speech Recognition

no code implementations13 Nov 2018 Senmao Wang, Pan Zhou, Wei Chen, Jia Jia, Lei Xie

End-to-end approaches have drawn much attention recently for significantly simplifying the construction of an automatic speech recognition (ASR) system.

automatic-speech-recognition Language Modelling +2

Modality Attention for End-to-End Audio-visual Speech Recognition

no code implementations13 Nov 2018 Pan Zhou, Wenwen Yang, Wei Chen, Yan-Feng Wang, Jia Jia

In this paper, we propose a novel multimodal attention based method for audio-visual speech recognition which could automatically learn the fused representation from both modalities based on their importance.

Audio-Visual Speech Recognition Robust Speech Recognition +1

An Online Attention-based Model for Speech Recognition

no code implementations13 Nov 2018 Ruchao Fan, Pan Zhou, Wei Chen, Jia Jia, Gang Liu

In previous work, researchers have shown that such architectures can acquire comparable results to state-of-the-art ASR systems, especially when using a bidirectional encoder and global soft attention (GSA) mechanism.

automatic-speech-recognition Language Modelling +2

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

1 code implementation5 Nov 2018 Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan, Guilherme Escudero, Théo Estienne, Richard Everson, Jonathan Fabrizio, Yong Fan, Longwei Fang, Xue Feng, Enzo Ferrante, Lucas Fidon, Martin Fischer, Andrew P. French, Naomi Fridman, Huan Fu, David Fuentes, Yaozong Gao, Evan Gates, David Gering, Amir Gholami, Willi Gierke, Ben Glocker, Mingming Gong, Sandra González-Villá, T. Grosges, Yuanfang Guan, Sheng Guo, Sudeep Gupta, Woo-Sup Han, Il Song Han, Konstantin Harmuth, Huiguang He, Aura Hernández-Sabaté, Evelyn Herrmann, Naveen Himthani, Winston Hsu, Cheyu Hsu, Xiaojun Hu, Xiaobin Hu, Yan Hu, Yifan Hu, Rui Hua, Teng-Yi Huang, Weilin Huang, Sabine Van Huffel, Quan Huo, Vivek HV, Khan M. Iftekharuddin, Fabian Isensee, Mobarakol Islam, Aaron S. Jackson, Sachin R. Jambawalikar, Andrew Jesson, Weijian Jian, Peter Jin, V Jeya Maria Jose, Alain Jungo, B Kainz, Konstantinos Kamnitsas, Po-Yu Kao, Ayush Karnawat, Thomas Kellermeier, Adel Kermi, Kurt Keutzer, Mohamed Tarek Khadir, Mahendra Khened, Philipp Kickingereder, Geena Kim, Nik King, Haley Knapp, Urspeter Knecht, Lisa Kohli, Deren Kong, Xiangmao Kong, Simon Koppers, Avinash Kori, Ganapathy Krishnamurthi, Egor Krivov, Piyush Kumar, Kaisar Kushibar, Dmitrii Lachinov, Tryphon Lambrou, Joon Lee, Chengen Lee, Yuehchou Lee, M Lee, Szidonia Lefkovits, Laszlo Lefkovits, James Levitt, Tengfei Li, Hongwei Li, Hongyang Li, Xiaochuan Li, Yuexiang Li, Heng Li, Zhenye Li, Xiaoyu Li, Zeju Li, Xiaogang Li, Wenqi Li, Zheng-Shen Lin, Fengming Lin, Pietro Lio, Chang Liu, Boqiang Liu, Xiang Liu, Mingyuan Liu, Ju Liu, Luyan Liu, Xavier Llado, Marc Moreno Lopez, Pablo Ribalta Lorenzo, Zhentai Lu, Lin Luo, Zhigang Luo, Jun Ma, Kai Ma, Thomas Mackie, Anant Madabushi, Issam Mahmoudi, Klaus H. Maier-Hein, Pradipta Maji, CP Mammen, Andreas Mang, B. S. Manjunath, Michal Marcinkiewicz, S McDonagh, Stephen McKenna, Richard McKinley, Miriam Mehl, Sachin Mehta, Raghav Mehta, Raphael Meier, Christoph Meinel, Dorit Merhof, Craig Meyer, Robert Miller, Sushmita Mitra, Aliasgar Moiyadi, David Molina-Garcia, Miguel A. B. Monteiro, Grzegorz Mrukwa, Andriy Myronenko, Jakub Nalepa, Thuyen Ngo, Dong Nie, Holly Ning, Chen Niu, Nicholas K Nuechterlein, Eric Oermann, Arlindo Oliveira, Diego D. C. Oliveira, Arnau Oliver, Alexander F. I. Osman, Yu-Nian Ou, Sebastien Ourselin, Nikos Paragios, Moo Sung Park, Brad Paschke, J. Gregory Pauloski, Kamlesh Pawar, Nick Pawlowski, Linmin Pei, Suting Peng, Silvio M. Pereira, Julian Perez-Beteta, Victor M. Perez-Garcia, Simon Pezold, Bao Pham, Ashish Phophalia, Gemma Piella, G. N. Pillai, Marie Piraud, Maxim Pisov, Anmol Popli, Michael P. Pound, Reza Pourreza, Prateek Prasanna, Vesna Prkovska, Tony P. Pridmore, Santi Puch, Élodie Puybareau, Buyue Qian, Xu Qiao, Martin Rajchl, Swapnil Rane, Michael Rebsamen, Hongliang Ren, Xuhua Ren, Karthik Revanuru, Mina Rezaei, Oliver Rippel, Luis Carlos Rivera, Charlotte Robert, Bruce Rosen, Daniel Rueckert, Mohammed Safwan, Mostafa Salem, Joaquim Salvi, Irina Sanchez, Irina Sánchez, Heitor M. Santos, Emmett Sartor, Dawid Schellingerhout, Klaudius Scheufele, Matthew R. Scott, Artur A. Scussel, Sara Sedlar, Juan Pablo Serrano-Rubio, N. Jon Shah, Nameetha Shah, Mazhar Shaikh, B. Uma Shankar, Zeina Shboul, Haipeng Shen, Dinggang Shen, Linlin Shen, Haocheng Shen, Varun Shenoy, Feng Shi, Hyung Eun Shin, Hai Shu, Diana Sima, M Sinclair, Orjan Smedby, James M. Snyder, Mohammadreza Soltaninejad, Guidong Song, Mehul Soni, Jean Stawiaski, Shashank Subramanian, Li Sun, Roger Sun, Jiawei Sun, Kay Sun, Yu Sun, Guoxia Sun, Shuang Sun, Yannick R Suter, Laszlo Szilagyi, Sanjay Talbar, DaCheng Tao, Zhongzhao Teng, Siddhesh Thakur, Meenakshi H Thakur, Sameer Tharakan, Pallavi Tiwari, Guillaume Tochon, Tuan Tran, Yuhsiang M. Tsai, Kuan-Lun Tseng, Tran Anh Tuan, Vadim Turlapov, Nicholas Tustison, Maria Vakalopoulou, Sergi Valverde, Rami Vanguri, Evgeny Vasiliev, Jonathan Ventura, Luis Vera, Tom Vercauteren, C. A. Verrastro, Lasitha Vidyaratne, Veronica Vilaplana, Ajeet Vivekanandan, Qian Wang, Chiatse J. Wang, Wei-Chung Wang, Duo Wang, Ruixuan Wang, Yuanyuan Wang, Chunliang Wang, Guotai Wang, Ning Wen, Xin Wen, Leon Weninger, Wolfgang Wick, Shaocheng Wu, Qiang Wu, Yihong Wu, Yong Xia, Yanwu Xu, Xiaowen Xu, Peiyuan Xu, Tsai-Ling Yang, Xiaoping Yang, Hao-Yu Yang, Junlin Yang, Haojin Yang, Guang Yang, Hongdou Yao, Xujiong Ye, Changchang Yin, Brett Young-Moxon, Jinhua Yu, Xiangyu Yue, Songtao Zhang, Angela Zhang, Kun Zhang, Xue-jie Zhang, Lichi Zhang, Xiaoyue Zhang, Yazhuo Zhang, Lei Zhang, Jian-Guo Zhang, Xiang Zhang, Tianhao Zhang, Sicheng Zhao, Yu Zhao, Xiaomei Zhao, Liang Zhao, Yefeng Zheng, Liming Zhong, Chenhong Zhou, Xiaobing Zhou, Fan Zhou, Hongtu Zhu, Jin Zhu, Ying Zhuge, Weiwei Zong, Jayashree Kalpathy-Cramer, Keyvan Farahani, Christos Davatzikos, Koen van Leemput, Bjoern Menze

This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.

Brain Tumor Segmentation Survival Prediction +1

Improving the Robustness of Speech Translation

no code implementations2 Nov 2018 Xiang Li, Haiyang Xue, Wei Chen, Yang Liu, Yang Feng, Qun Liu

Although neural machine translation (NMT) has achieved impressive progress recently, it is usually trained on the clean parallel data set and hence cannot work well when the input sentence is the production of the automatic speech recognition (ASR) system due to the enormous errors in the source.

automatic-speech-recognition Machine Translation +1

Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

no code implementations NeurIPS 2017 Yue Wang, Wei Chen, Yu-Ting Liu, Zhi-Ming Ma, Tie-Yan Liu

(2) The convergence rate is determined by the step size, with the mixing time of the Markov process as the coefficient.

Capacity Control of ReLU Neural Networks by Basis-path Norm

no code implementations19 Sep 2018 Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu

Motivated by this, we propose a new norm \emph{Basis-path Norm} based on a group of linearly independent paths to measure the capacity of neural networks more accurately.

BézierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters

no code implementations27 Aug 2018 Wei Chen, Mark Fuge

Many real-world objects are designed by smooth curves, especially in the domain of aerospace and ship, where aerodynamic shapes (e. g., airfoils) and hydrodynamic shapes (e. g., hulls) are designed.


1 code implementation26 Aug 2018 Xiaolin Li, Zijiang Yang, L. Catherine Brinson, Alok Choudhary, Ankit Agrawal, Wei Chen

Due to the special design of the network architecture, the proposed methodology is able to identify the latent (design) variables with desired dimensionality, as well as capturing complex material microstructural characteristics.

Dimensionality Reduction

Semi-Supervised Disfluency Detection

no code implementations COLING 2018 Feng Wang, Wei Chen, Zhen Yang, Qianqian Dong, Shuang Xu, Bo Xu

While the disfluency detection has achieved notable success in the past years, it still severely suffers from the data scarcity.

Machine Translation Question Answering

Towards Binary-Valued Gates for Robust LSTM Training

1 code implementation ICML 2018 Zhuohan Li, Di He, Fei Tian, Wei Chen, Tao Qin, Li-Wei Wang, Tie-Yan Liu

Long Short-Term Memory (LSTM) is one of the most widely used recurrent structures in sequence modeling.

SupportNet: solving catastrophic forgetting in class incremental learning with support data

1 code implementation8 Jun 2018 Yu Li, Zhongxiao Li, Lizhong Ding, Yijie Pan, Chao Huang, Yuhui Hu, Wei Chen, Xin Gao

A plain well-trained deep learning model often does not have the ability to learn new knowledge without forgetting the previously learned knowledge, which is known as catastrophic forgetting.

class-incremental learning Incremental Learning

Peperomia at SemEval-2018 Task 2: Vector Similarity Based Approach for Emoji Prediction

no code implementations SEMEVAL 2018 Jing Chen, Dechuan Yang, Xilian Li, Wei Chen, Tengjiao Wang

First the distributed representation (tweet vector) for each tweet is generated, then the similarity between this tweet vector and each emoji{'}s embedding is evaluated.

Classification General Classification +3

Differential Equations for Modeling Asynchronous Algorithms

no code implementations8 May 2018 Li He, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

Then we conduct theoretical analysis on the convergence rates of ASGD algorithm based on the continuous approximation.

Unsupervised Neural Machine Translation with Weight Sharing

1 code implementation ACL 2018 Zhen Yang, Wei Chen, Feng Wang, Bo Xu

Unsupervised neural machine translation (NMT) is a recently proposed approach for machine translation which aims to train the model without using any labeled data.

Machine Translation

Thompson Sampling for Combinatorial Semi-Bandits

no code implementations ICML 2018 Siwei Wang, Wei Chen

When the reward function is linear, the regret of the TS algorithm achieves a better bound $O(m\log K_{\max}\log T / \Delta_{\min})$.

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation

no code implementations27 Feb 2018 Huishuai Zhang, Wei Chen, Tie-Yan Liu

This inconsistence of gradient magnitude across different layers renders optimization of deep neural network with a single learning rate problematic.

Scalable Influence Maximization with General Marketing Strategies

no code implementations13 Feb 2018 Ruihan Wu, Zheng Yu, Wei Chen

In this paper, we study scalable algorithms for influence maximization with general marketing strategies (IM-GMS), in which a marketing strategy mix is modeled as a vector $\mathbf{x}=(x_1, \ldots, x_d)$ and could activate a node $v$ in the social network with probability $h_v(\mathbf{x})$.

Social and Information Networks Data Structures and Algorithms