b'Yi Ma'

research

∙ 06/18/2022

Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games

We consider the problem of learning discriminative representations for d...

Druv Pai, et al. ∙

research

∙ 04/06/2022

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations

Deep Reinforcement Learning (DRL) has been a promising solution to many ...

Tong Sang, et al. ∙

research

∙ 03/31/2022

Efficient Maximal Coding Rate Reduction by Variational Forms

The principle of Maximal Coding Rate Reduction (MCR^2) has recently been...

Christina Baek, et al. ∙

research

∙ 03/28/2022

A Novel Multi-Task Learning Empowered Codebook Design for Downlink SCMA Networks

Sparse code multiple access (SCMA) is a promising code-domain non-orthog...

Qu Luo, et al. ∙

research

∙ 02/11/2022

Predicting Out-of-Distribution Error with the Projection Norm

We propose a metric – Projection Norm – to predict a model's performance...

Yaodong Yu, et al. ∙

research

∙ 02/11/2022

Incremental Learning of Structured Memory via Closed-Loop Transcription

This work proposes a minimal computational model for learning a structur...

Shengbang Tong, et al. ∙

research

∙ 01/04/2022

DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression

Scalable coding, which can adapt to channel bandwidth variation, perform...

Yi Ma, et al. ∙

research

∙ 11/12/2021

Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction

This work proposes a new computational framework for learning an explici...

Xili Dai, et al. ∙

research

∙ 10/03/2021

PL-EESR: Perceptual Loss Based END-TO-END Robust Speaker Representation Extraction

Speech enhancement aims to improve the perceptual quality of the speech ...

Yi Ma, et al. ∙

research

∙ 09/11/2021

Hermite Expansion Model and LMMSE Analysis for Low-Resolution Quantized MIMO Detection

In this paper, the Hermite polynomials are employed to study linear appr...

Lifu Liu, et al. ∙

research

∙ 08/21/2021

Correlation-Based Device Energy-Efficient Dynamic Multi-Task Offloading for Mobile Edge Computing

Task offloading to mobile edge computing (MEC) has emerged as a key tech...

Siqi Zhang, et al. ∙

research

∙ 08/18/2021

A Non-Stationary Channel Model with Correlated NLoS/LoS States for ELAA-mMIMO

In this paper, a novel spatially non-stationary channel model is propose...

Jiuyu Liu, et al. ∙

research

∙ 07/08/2021

Computational Benefits of Intermediate Rewards for Hierarchical Planning

Many hierarchical reinforcement learning (RL) applications have empirica...

Yuexiang Zhai, et al. ∙

research

∙ 06/30/2021

On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging

We study the stochastic bilinear minimax optimization problem, presentin...

Chris Junchi Li, et al. ∙

research

∙ 06/18/2021

Learning and Meshing from Deep Implicit Surface Networks Using an Efficient Implementation of Analytic Marching

Reconstruction of object or scene surfaces has tremendous applications i...

Jiabao Lei, et al. ∙

research

∙ 05/21/2021

ReduNet: A White-box Deep Network from the Principle of Maximizing Rate Reduction

This work attempts to provide a plausible theoretical framework that aim...

Kwan Ho Ryan Chan, et al. ∙

research

∙ 05/04/2021

End-to-End Learning for Uplink MU-SIMO Joint Transmitter and Non-Coherent Receiver Design in Fading Channels

In this paper, a novel end-to-end learning approach, namely JTRD-Net, is...

Songyan Xue, et al. ∙

research

∙ 04/22/2021

Fully Convolutional Line Parsing

We present a one-stage Fully Convolutional Line Parsing network (F-Clip)...

Xili Dai, et al. ∙

research

∙ 04/16/2021

Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

Single-image room layout reconstruction aims to reconstruct the enclosed...

Cheng Yang, et al. ∙

research

∙ 03/17/2021

Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition

Adversarially trained models exhibit a large generalization gap: they ca...

Yaodong Yu, et al. ∙

research

∙ 03/07/2021

Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities

The optimization problems associated with training generative adversaria...

Chaobing Song, et al. ∙

research

∙ 11/30/2020

Incremental Learning via Rate Reduction

Current deep learning architectures suffer from catastrophic forgetting,...

Ziyang Wu, et al. ∙

research

∙ 10/27/2020

Deep Networks from the Principle of Rate Reduction

This work attempts to interpret modern deep (convolutional) networks fro...

Kwan Ho Ryan Chan, et al. ∙

research

∙ 08/07/2020

HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures

We present HoliCity, a city-scale 3D dataset with rich structural inform...

Yichao Zhou, et al. ∙

research

∙ 08/05/2020

Learning Long-term Visual Dynamics with Region Proposal Interaction Networks

Learning long-term dynamics models is the key to understanding physical ...

Haozhi Qi, et al. ∙

research

∙ 07/15/2020

Learning to Parse Wireframes in Images of Man-Made Environments

In this paper, we propose a learning-based approach to the task of autom...

Kun Huang, et al. ∙

research

∙ 06/30/2020

Deep Isometric Learning for Visual Recognition

Initialization, normalization, and skip connections are believed to be t...

Haozhi Qi, et al. ∙

research

∙ 06/29/2020

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising

In E-commerce, advertising is essential for merchants to reach their tar...

Xiaotian Hao, et al. ∙

research

∙ 06/18/2020

Stochastic Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization

In this paper, we introduce a simplified and unified method for finite-s...

Chaobing Song, et al. ∙

research

∙ 06/17/2020

Learning to Detect 3D Reflection Symmetry for Single-View Reconstruction

3D reconstruction from a single RGB image is a challenging problem in co...

Yichao Zhou, et al. ∙

research

∙ 06/16/2020

Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization

Recent advances have shown that implicit bias of gradient descent on ove...

Chong You, et al. ∙

research

∙ 06/15/2020

Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction

To learn intrinsic low-dimensional structures from high-dimensional data...

Yaodong Yu, et al. ∙

research

∙ 05/09/2020

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising

Bipartite b-matching is fundamental in algorithm design, and has been wi...

Xiaotian Hao, et al. ∙

research

∙ 04/14/2020

On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems

This paper aims to handle the joint transmitter and noncoherent receiver...

Songyan Xue, et al. ∙

research

∙ 04/01/2020

A Modular Neural Network Based Deep Learning Approach for MIMO Signal Detection

In this paper, we reveal that artificial neural network (ANN) assisted m...

Songyan Xue, et al. ∙

research

∙ 02/26/2020

Rethinking Bias-Variance Trade-off for Generalization of Neural Networks

The classical bias-variance trade-off predicts that bias decreases and v...

Zitong Yang, et al. ∙

research

∙ 02/18/2020

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

Reinforcement learning agents usually learn from scratch, which requires...

Peng Zhang, et al. ∙

research

∙ 02/03/2020

An Actor-Critic-Based UAV-BSs Deployment Method for Dynamic Environments

In this paper, the real-time deployment of unmanned aerial vehicles (UAV...

Zhiwei Chen, et al. ∙

research

∙ 10/14/2019

NeurVPS: Neural Vanishing Point Scanning via Conic Convolution

We present a simple yet effective end-to-end trainable deep network with...

Yichao Zhou, et al. ∙

research

∙ 07/21/2019

Spectral-based Graph Convolutional Network for Directed Graphs

Graph convolutional networks(GCNs) have become the most popular approach...

Yi Ma, et al. ∙

research

∙ 06/06/2019

Complete Dictionary Learning via ℓ^4-Norm Maximization over the Orthogonal Group

This paper considers the fundamental problem of learning a complete (ort...

Yuexiang Zhai, et al. ∙

research

∙ 06/03/2019

Towards Unified Acceleration of High-Order Algorithms under Hölder Continuity and Uniform Convexity

In this paper, through a very intuitive vanilla proximal method perspec...

Chaobing Song, et al. ∙

research

∙ 05/17/2019

Learning to Reconstruct 3D Manhattan Wireframes from a Single Image

In this paper, we propose a method to obtain a compact and accurate 3D w...

Yichao Zhou, et al. ∙

research

∙ 05/08/2019

End-to-End Wireframe Parsing

We present a conceptually simple yet effective algorithm to detect wiref...

Yichao Zhou, et al. ∙

research

∙ 10/26/2018

Fine-grained Video Categorization with Redundancy Reduction Attention

For fine-grained categorization tasks, videos could serve as a better so...

Chen Zhu, et al. ∙

research

∙ 02/11/2018

TARM: A Turbo-type Algorithm for Affine Rank Minimization

The affine rank minimization (ARM) problem arises in many real-world app...

Zhipeng Xue, et al. ∙

research

∙ 12/20/2017

Symbol-Level Selective Full-Duplex Relaying with Power and Location Optimization

In this paper, a symbol-level selective transmission for full-duplex (FD...

Jiancao Hou, et al. ∙

research

∙ 08/07/2017

Structured Attentions for Visual Question Answering

Visual attention, which assigns weights to image regions according to th...

Chen Zhu, et al. ∙

research

∙ 07/08/2016

Graph Construction with Label Information for Semi-Supervised Learning

In the literature, most existing graph-based semi-supervised learning (S...

Liansheng Zhuang, et al. ∙

research

∙ 06/15/2015

Automatic Layer Separation using Light Field Imaging

We propose a novel approach that jointly removes reflection or transluce...

Qiaosong Wang, et al. ∙

Yi Ma

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