b'Tong Zhang'

research

∙ 07/17/2019

DeepSqueeze: Decentralization Meets Error-Compensated Compression

Communication is a key bottleneck in distributed training. Recently, an ...

0 Hanlin Tang, et al. ∙

research

∙ 07/17/2019

DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

Communication is a key bottleneck in distributed training. Recently, an ...

0 Hanlin Tang, et al. ∙

research

∙ 07/11/2019

Optimal Feature Transport for Cross-View Image Geo-Localization

This paper addresses the problem of cross-view image based localization,...

0 Yujiao Shi, et al. ∙

research

∙ 05/28/2019

Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks

Neuroscientists have enjoyed much success in understanding brain functio...

0 Kean Ming Tan, et al. ∙

research

∙ 05/15/2019

DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

A standard approach in large scale machine learning is distributed stoch...

0 Hanlin Tang, et al. ∙

research

∙ 05/09/2019

MAP Inference via L2-Sphere Linear Program Reformulation

Maximum a posteriori (MAP) inference is an important task for graphical ...

0 Baoyuan Wu, et al. ∙

research

∙ 05/01/2019

NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks

Powerful adversarial attack methods are vital for understanding how to c...

10 Yandong Li, et al. ∙

research

∙ 04/24/2019

Neural Collaborative Subspace Clustering

We introduce the Neural Collaborative Subspace Clustering, a neural mode...

0 Tong Zhang, et al. ∙

research

∙ 04/09/2019

Efficient Decision-based Black-box Adversarial Attacks on Face Recognition

Face recognition has obtained remarkable progress in recent years due to...

0 Yinpeng Dong, et al. ∙

research

∙ 02/15/2019

Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement

With the promising progress of deep neural networks, layer aggregation h...

0 Zi-Yi Dou, et al. ∙

research

∙ 02/01/2019

Sharp Analysis for Nonconvex SGD Escaping from Saddle Points

In this paper, we prove that the simplest Stochastic Gradient Descent (S...

0 Cong Fang, et al. ∙

research

∙ 01/07/2019

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

In existing visual representation learning tasks, deep convolutional neu...

0 Baoyuan Wu, et al. ∙

research

∙ 12/29/2018

Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack

Zeroth-order optimization or derivative-free optimization is an importan...

0 Haishan Ye, et al. ∙

research

∙ 12/06/2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning

Despite the increasing interest in multi-agent reinforcement learning (M...

2 Kaiqing Zhang, et al. ∙

research

∙ 11/30/2018

Cross-database non-frontal facial expression recognition based on transductive deep transfer learning

Cross-database non-frontal expression recognition is a very meaningful b...

2 Keyu Yan, et al. ∙

research

∙ 11/21/2018

Neural Machine Translation with Adequacy-Oriented Learning

Although Neural Machine Translation (NMT) models have advanced state-of-...

10 Xiang Kong, et al. ∙

research

∙ 11/06/2018

Super-Identity Convolutional Neural Network for Face Hallucination

Face hallucination is a generative task to super-resolve the facial imag...

4 Kaipeng Zhang, et al. ∙

research

∙ 11/03/2018

Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity

Regularized empirical risk minimization problem with linear predictor ap...

0 Conghui Tan, et al. ∙

research

∙ 11/02/2018

Scalable Deep k-Subspace Clustering

Subspace clustering algorithms are notorious for their scalability issue...

0 Tong Zhang, et al. ∙

research

∙ 11/02/2018

Proximal Gradient Method for Manifold Optimization

This paper considers manifold optimization problems with nonsmooth and n...

0 Shixiang Chen, et al. ∙

research

∙ 10/24/2018

Multi-Head Attention with Disagreement Regularization

Multi-head attention is appealing for the ability to jointly attend to i...

0 Jian Li, et al. ∙

research

∙ 10/24/2018

Modeling Localness for Self-Attention Networks

Self-attention networks have proven to be of profound value for its stre...

0 Baosong Yang, et al. ∙

research

∙ 10/24/2018

Exploiting Deep Representations for Neural Machine Translation

Advanced neural machine translation (NMT) models generally implement enc...

0 Zi-Yi Dou, et al. ∙

research

∙ 10/17/2018

Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition

As facial appearance is subject to significant intra-class variations ca...

0 Yitong Wang, et al. ∙

research

∙ 10/12/2018

Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry

Combining cameras and inertial measurement units (IMUs) has been proven ...

0 Yonggen Ling, et al. ∙

research

∙ 10/10/2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Most existing deep reinforcement learning (DRL) frameworks consider eith...

0 Jiechao Xiong, et al. ∙

research

∙ 09/25/2018

Fully Implicit Online Learning

Regularized online learning is widely used in machine learning. In this ...

8 Chaobing Song, et al. ∙

research

∙ 09/19/2018

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game

Starcraft II (SCII) is widely considered as the most challenging Real Ti...

10 Peng Sun, et al. ∙

research

∙ 09/17/2018

A convex formulation for high-dimensional sparse sliced inverse regression

Sliced inverse regression is a popular tool for sufficient dimension red...

2 Kean Ming Tan, et al. ∙

research

∙ 09/14/2018

Adaptive Sampling Towards Fast Graph Representation Learning

Graph Convolutional Networks (GCNs) have become a crucial tool on learni...

0 Wenbing Huang, et al. ∙

research

∙ 08/29/2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

In this paper, we propose to adopt the diffusion approximation tools to ...

4 Chris Junchi Li, et al. ∙

research

∙ 08/10/2018

End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning

We study active object tracking, where a tracker takes visual observatio...

2 Wenhan Luo, et al. ∙

research

∙ 08/05/2018

Video Re-localization

Many methods have been developed to help people find the video contents ...

4 Yang Feng, et al. ∙

research

∙ 07/26/2018

Recurrent Fusion Network for Image Captioning

Recently, much advance has been made in image captioning, and an encoder...

0 Wenhao Jiang, et al. ∙

research

∙ 07/23/2018

Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks

Recent studies on unsupervised image-to-image translation have made rema...

0 Minjun Li, et al. ∙

research

∙ 07/07/2018

When Work Matters: Transforming Classical Network Structures to Graph CNN

Numerous pattern recognition applications can be formed as learning from...

0 Wenting Zhao, et al. ∙

research

∙ 07/04/2018

SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator

In this paper, we propose a new technique named Stochastic Path-Integrat...

0 Cong Fang, et al. ∙

research

∙ 06/21/2018

Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization

Large-scale distributed optimization is of great importance in various a...

0 Jiaxiang Wu, et al. ∙

research

∙ 05/22/2018

Safe Element Screening for Submodular Function Minimization

Submodular functions are discrete analogs of convex functions, which hav...

0 Weizhong Zhang, et al. ∙

research

∙ 04/19/2018

Incorporating Pseudo-Parallel Data for Quantifiable Sequence Editing

In the task of quantifiable sequence editing (QuaSE), a model needs to e...

0 Yi Liao, et al. ∙

research

∙ 04/04/2018

Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset

Nowadays, billions of videos are online ready to be viewed and shared. A...

0 Xinpeng Chen, et al. ∙

research

∙ 03/29/2018

Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

The success of current deep saliency detection methods heavily depends o...

0 Jing Zhang, et al. ∙

research

∙ 03/27/2018

Tensor graph convolutional neural network

In this paper, we propose a novel tensor graph convolutional neural netw...

0 Tong Zhang, et al. ∙

research

∙ 03/17/2018

Decentralization Meets Quantization

Optimizing distributed learning systems is an art of balancing between c...

0 Hanlin Tang, et al. ∙

research

∙ 02/23/2018

Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents

We consider the problem of fully decentralized multi-agent reinforcement...

0 Kaiqing Zhang, et al. ∙

research

∙ 01/19/2018

Composite Functional Gradient Learning of Generative Adversarial Models

Generative adversarial networks (GAN) have become popular for generating...

0 Rie Johnson, et al. ∙

research

∙ 01/10/2018

Translating Pro-Drop Languages with Reconstruction Models

Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...

0 Longyue Wang, et al. ∙

research

∙ 11/26/2017

Learning to Remember Translation History with a Continuous Cache

Existing neural machine translation (NMT) models generally translate sen...

0 Zhaopeng Tu, et al. ∙

research

∙ 11/02/2017

Candidates v.s. Noises Estimation for Large Multi-Class Classification Problem

This paper proposes a method for multi-class classification problems, wh...

0 Lei Han, et al. ∙

research

∙ 10/26/2017

Gradient Sparsification for Communication-Efficient Distributed Optimization

Modern large scale machine learning applications require stochastic opti...

0 Jianqiao Wangni, et al. ∙

Tong Zhang

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