b'Kun Yuan'

research

∙ 08/01/2023

Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment

Video quality assessment (VQA) has attracted growing attention in recent...

0 Hongbo Liu, et al. ∙

research

∙ 07/31/2023

Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessment

Video Quality Assessment (VQA), which aims to predict the perceptual qua...

0 Kun Yuan, et al. ∙

research

∙ 07/27/2023

Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures

Recent advancements in surgical computer vision applications have been d...

0 Kun Yuan, et al. ∙

research

∙ 07/19/2023

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhance...

0 Xiaohong Liu, et al. ∙

research

∙ 06/28/2023

Momentum Benefits Non-IID Federated Learning Simply and Provably

Federated learning is a powerful paradigm for large-scale machine learni...

0 Ziheng Cheng, et al. ∙

research

∙ 06/01/2023

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm

Decentralized Stochastic Gradient Descent (SGD) is an emerging neural ne...

0 Lisang Ding, et al. ∙

research

∙ 05/25/2023

Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?

Communication compression is a common technique in distributed optimizat...

0 Yutong He, et al. ∙

research

∙ 05/12/2023

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression

Communication compression is an essential strategy for alleviating commu...

0 Yutong He, et al. ∙

research

∙ 04/13/2023

Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment

Video quality assessment (VQA) aims to simulate the human perception of ...

0 Kai Zhao, et al. ∙

research

∙ 03/15/2023

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

While most recent autonomous driving system focuses on developing percep...

0 Lei Yang, et al. ∙

research

∙ 03/01/2023

Quality-aware Pre-trained Models for Blind Image Quality Assessment

Blind image quality assessment (BIQA) aims to automatically evaluate the...

0 Kai Zhao, et al. ∙

research

∙ 02/13/2023

CholecTriplet2022: Show me a tool and tell me the triplet – an endoscopic vision challenge for surgical action triplet detection

Formalizing surgical activities as triplets of the used instruments, act...

1 Chinedu Innocent Nwoye, et al. ∙

research

∙ 11/01/2022

Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks

Decentralized optimization with time-varying networks is an emerging par...

0 Xinmeng Huang, et al. ∙

research

∙ 10/14/2022

Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate

Decentralized optimization is an emerging paradigm in distributed learni...

0 Zhuoqing Song, et al. ∙

research

∙ 10/14/2022

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization

Decentralized optimization is effective to save communication in large-s...

0 Kun Yuan, et al. ∙

research

∙ 10/10/2022

On the Performance of Gradient Tracking with Local Updates

We study the decentralized optimization problem where a network of n age...

0 Edward Duc Hien Nguyen, et al. ∙

research

∙ 06/08/2022

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression

Recent advances in distributed optimization and learning have shown that...

0 Xinmeng Huang, et al. ∙

research

∙ 05/13/2022

Heavy-Tail Phenomenon in Decentralized SGD

Recent theoretical studies have shown that heavy-tails can emerge in sto...

0 Mert Gurbuzbalaban, et al. ∙

research

∙ 04/06/2022

ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks

Face inpainting aims to complete the corrupted regions of the face image...

0 Zhuojie Wu, et al. ∙

research

∙ 11/26/2021

Self-supervised Correlation Mining Network for Person Image Generation

Person image generation aims to perform non-rigid deformation on source ...

0 Zijian Wang, et al. ∙

research

∙ 11/08/2021

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning

Decentralized algorithm is a form of computation that achieves a global ...

25 Bicheng Ying, et al. ∙

research

∙ 10/26/2021

Exponential Graph is Provably Efficient for Decentralized Deep Training

Decentralized SGD is an emerging training method for deep learning known...

7 Bicheng Ying, et al. ∙

research

∙ 10/19/2021

A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning

We study the consensus decentralized optimization problem where the obje...

0 Sulaiman A. Alghunaim, et al. ∙

research

∙ 08/10/2021

Decentralized Composite Optimization with Compression

Decentralized optimization and communication compression have exhibited ...

0 Yao Li, et al. ∙

research

∙ 05/19/2021

Accelerating Gossip SGD with Periodic Global Averaging

Communication overhead hinders the scalability of large-scale distribute...

7 Yiming Chen, et al. ∙

research

∙ 05/17/2021

Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD

We consider decentralized stochastic optimization problems where a netwo...

0 Kun Yuan, et al. ∙

research

∙ 04/25/2021

On the Comparison between Cyclic Sampling and Random Reshuffling

When applying a stochastic/incremental algorithm, one must choose the or...

14 Xinmeng Huang, et al. ∙

research

∙ 04/24/2021

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training

The scale of deep learning nowadays calls for efficient distributed trai...

20 Kun Yuan, et al. ∙

research

∙ 03/30/2021

Differentiable Network Adaption with Elastic Search Space

In this paper we propose a novel network adaption method called Differen...

0 Shaopeng Guo, et al. ∙

research

∙ 03/22/2021

Incorporating Convolution Designs into Visual Transformers

Motivated by the success of Transformers in natural language processing ...

0 Kun Yuan, et al. ∙

research

∙ 02/08/2021

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Sparsity in Deep Neural Networks (DNNs) has been widely studied to compr...

0 Aojun Zhou, et al. ∙

research

∙ 10/02/2020

Dynamic Graph: Learning Instance-aware Connectivity for Neural Networks

One practice of employing deep neural networks is to apply the same arch...

1 Kun Yuan, et al. ∙

research

∙ 08/19/2020

Learning Connectivity of Neural Networks from a Topological Perspective

Seeking effective neural networks is a critical and practical field in d...

39 Kun Yuan, et al. ∙

research

∙ 05/26/2019

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs

Despite remarkable empirical success, the training dynamics of generativ...

10 Ernest K. Ryu, et al. ∙

research

∙ 05/20/2019

A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization

Decentralized optimization is a promising paradigm that finds various ap...

0 Sulaiman A. Alghunaim, et al. ∙

research

∙ 03/26/2019

On the Performance of Exact Diffusion over Adaptive Networks

Various bias-correction methods such as EXTRA, DIGing, and exact diffusi...

8 Kun Yuan, et al. ∙

research

∙ 10/21/2018

Dynamic Average Diffusion with randomized Coordinate Updates

This work derives and analyzes an online learning strategy for tracking ...

0 Bicheng Ying, et al. ∙

research

∙ 10/17/2018

Multi-Agent Fully Decentralized Value Function Learning with Linear Convergence Rates

This work develops a fully decentralized multi-agent algorithm for polic...

0 Lucas Cassano, et al. ∙

research

∙ 10/17/2018

Multi-Agent Fully Decentralized Off-Policy Learning with Linear Convergence Rates

In this paper we develop a fully decentralized algorithm for policy eval...

0 Lucas Cassano, et al. ∙

research

∙ 05/29/2018

Learning Under Distributed Features

This work studies the problem of learning under both large data and larg...

0 Bicheng Ying, et al. ∙

research

∙ 04/18/2018

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

This paper addresses consensus optimization problems in a multi-agent ne...

0 Xianghui Mao, et al. ∙

research

∙ 04/18/2018

A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

This paper addresses consensus optimization problem in a multi-agent net...

0 Wotao Yin, et al. ∙

research

∙ 03/21/2018

Stochastic Learning under Random Reshuffling

In empirical risk optimization, it has been observed that stochastic gra...

0 Bicheng Ying, et al. ∙

research

∙ 08/04/2017

Efficient Variance-Reduced Learning for Fully Decentralized On-Device Intelligence

This work develops a fully decentralized variance-reduced learning algor...

0 Kun Yuan, et al. ∙

research

∙ 08/04/2017

Convergence of Variance-Reduced Stochastic Learning under Random Reshuffling

Several useful variance-reduced stochastic gradient algorithms, such as ...

0 Bicheng Ying, et al. ∙

research

∙ 03/14/2016

On the Influence of Momentum Acceleration on Online Learning

The article examines in some detail the convergence rate and mean-square...

0 Kun Yuan, et al. ∙

research

∙ 02/24/2016

Online Dual Coordinate Ascent Learning

The stochastic dual coordinate-ascent (S-DCA) technique is a useful alte...

0 Bicheng Ying, et al. ∙

Kun Yuan

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