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07/17/2019
DeepSqueeze: Decentralization Meets Error-Compensated Compression
Communication is a key bottleneck in distributed training. Recently, an ...
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07/17/2019
DeepSqueeze: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression
Communication is a key bottleneck in distributed training. Recently, an ...
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07/11/2019
Optimal Feature Transport for Cross-View Image Geo-Localization
This paper addresses the problem of cross-view image based localization,...
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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...
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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...
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05/09/2019
MAP Inference via L2-Sphere Linear Program Reformulation
Maximum a posteriori (MAP) inference is an important task for graphical ...
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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...
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04/24/2019
Neural Collaborative Subspace Clustering
We introduce the Neural Collaborative Subspace Clustering, a neural mode...
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04/09/2019
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition
Face recognition has obtained remarkable progress in recent years due to...
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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...
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02/01/2019
Sharp Analysis for Nonconvex SGD Escaping from Saddle Points
In this paper, we prove that the simplest Stochastic Gradient Descent (S...
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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...
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12/29/2018
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack
Zeroth-order optimization or derivative-free optimization is an importan...
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12/06/2018
Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning
Despite the increasing interest in multi-agent reinforcement learning (M...
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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...
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11/21/2018
Neural Machine Translation with Adequacy-Oriented Learning
Although Neural Machine Translation (NMT) models have advanced state-of-...
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11/06/2018
Super-Identity Convolutional Neural Network for Face Hallucination
Face hallucination is a generative task to super-resolve the facial imag...
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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...
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11/02/2018
Scalable Deep k-Subspace Clustering
Subspace clustering algorithms are notorious for their scalability issue...
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11/02/2018
Proximal Gradient Method for Manifold Optimization
This paper considers manifold optimization problems with nonsmooth and n...
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10/24/2018
Multi-Head Attention with Disagreement Regularization
Multi-head attention is appealing for the ability to jointly attend to i...
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10/24/2018
Modeling Localness for Self-Attention Networks
Self-attention networks have proven to be of profound value for its stre...
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10/24/2018
Exploiting Deep Representations for Neural Machine Translation
Advanced neural machine translation (NMT) models generally implement enc...
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10/17/2018
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
As facial appearance is subject to significant intra-class variations ca...
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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 ...
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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...
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09/25/2018
Fully Implicit Online Learning
Regularized online learning is widely used in machine learning. In this ...
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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...
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09/17/2018
A convex formulation for high-dimensional sparse sliced inverse regression
Sliced inverse regression is a popular tool for sufficient dimension red...
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09/14/2018
Adaptive Sampling Towards Fast Graph Representation Learning
Graph Convolutional Networks (GCNs) have become a crucial tool on learni...
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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 ...
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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...
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08/05/2018
Video Re-localization
Many methods have been developed to help people find the video contents ...
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07/26/2018
Recurrent Fusion Network for Image Captioning
Recently, much advance has been made in image captioning, and an encoder...
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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...
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07/07/2018
When Work Matters: Transforming Classical Network Structures to Graph CNN
Numerous pattern recognition applications can be formed as learning from...
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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...
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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...
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05/22/2018
Safe Element Screening for Submodular Function Minimization
Submodular functions are discrete analogs of convex functions, which hav...
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04/19/2018
Incorporating Pseudo-Parallel Data for Quantifiable Sequence Editing
In the task of quantifiable sequence editing (QuaSE), a model needs to e...
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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...
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03/29/2018
Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective
The success of current deep saliency detection methods heavily depends o...
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03/27/2018
Tensor graph convolutional neural network
In this paper, we propose a novel tensor graph convolutional neural netw...
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03/17/2018
Decentralization Meets Quantization
Optimizing distributed learning systems is an art of balancing between c...
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02/23/2018
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
We consider the problem of fully decentralized multi-agent reinforcement...
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01/19/2018
Composite Functional Gradient Learning of Generative Adversarial Models
Generative adversarial networks (GAN) have become popular for generating...
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01/10/2018
Translating Pro-Drop Languages with Reconstruction Models
Pronouns are frequently omitted in pro-drop languages, such as Chinese, ...
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11/26/2017
Learning to Remember Translation History with a Continuous Cache
Existing neural machine translation (NMT) models generally translate sen...
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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...
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10/26/2017