Global Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays. - Kun Yuan 001; Jinde Cao (ISNN (1), 2004)

An analysis of global asymptotic stability of delayed Cohen-Grossberg neural networks via nonsmooth analysis. - Kun Yuan 001; Jinde Cao (IEEE Trans. Circuits Syst. I Regul. Pap., 2005)

Exponential stability and periodic solutions of fuzzy cellular neural networks with time-varying delays. - Kun Yuan 001; Jinde Cao; Jianming Deng (Neurocomputing, 2006)

Global Asymptotical Stability of Recurrent Neural Networks With Multiple Discrete Delays and Distributed Delays. - Jinde Cao; Kun Yuan 001; Han-Xiong Li (IEEE Trans. Neural Networks, 2006)

Robust Stability of Switched Cohen-Grossberg Neural Networks With Mixed Time-Varying Delays. - Kun Yuan 001; Jinde Cao; Han-Xiong Li (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Robust Stabilization of the Distributed Parameter System With Time Delay via Fuzzy Control. - Kun Yuan 001; Han-Xiong Li; Jinde Cao (IEEE Trans. Fuzzy Syst., 2008)

Synchronization of Coupled Networks with Mixed Delays by Intermittent Control. - Kun Yuan 001; Jinde Cao; Shumin Fei (J. Appl. Math., 2012)

A linearized bregman algorithm for decentralized basis pursuit. - Kun Yuan 001; Qing Ling 001; Wotao Yin; Alejandro Ribeiro (EUSIPCO, 2013)

Linearly convergent decentralized consensus optimization with the alternating direction method of multipliers. - Wei Shi 010; Qing Ling 001; Kun Yuan 001; Gang Wu 011; Wotao Yin (ICASSP, 2013)

Partial synchronization of the distributed parameter system with time delay via fuzzy control. - Kun Yuan 001; Shumin Fei; Jinde Cao (IMA J. Math. Control. Inf., 2014)

On the Linear Convergence of the ADMM in Decentralized Consensus Optimization. - Wei Shi 010; Qing Ling 001; Kun Yuan 001; Gang Wu 011; Wotao Yin (IEEE Trans. Signal Process., 2014)

A decentralised linear programming approach to energy-efficient event detection. - Kun Yuan 001; Qing Ling 001; Zhi Tian (Int. J. Sens. Networks, 2015)

Communication-Efficient Decentralized Event Monitoring in Wireless Sensor Networks. - Kun Yuan 001; Qing Ling 001; Zhi Tian (IEEE Trans. Parallel Distributed Syst., 2015)

Online dual coordinate ascent learning. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (EUSIPCO, 2016)

Stochastic gradient descent with finite samples sizes. - Kun Yuan 001; Bicheng Ying; Stefan Vlaski; Ali H. Sayed (MLSP, 2016)

Cooperative tracking for nonlinear multi-agent systems with hybrid time-delayed protocol. - Jian-Qiang Hu; Jinde Cao; Kun Yuan 001; Tasawar Hayat (Neurocomputing, 2016)

On the Influence of Momentum Acceleration on Online Learning. - Kun Yuan 001; Bicheng Ying; Ali H. Sayed (J. Mach. Learn. Res., 2016)

On the Convergence of Decentralized Gradient Descent. - Kun Yuan 001; Qing Ling 001; Wotao Yin (SIAM J. Optim., 2016)

Decentralized exact coupled optimization. - Sulaiman A. Alghunaim; Kun Yuan 001; Ali H. Sayed (Allerton, 2017)

Exact diffusion strategy for optimization by networked agents. - Kun Yuan 001; Bicheng Ying; Xiaochuan Zhao; Ali H. Sayed (EUSIPCO, 2017)

On the performance of random reshuffling in stochastic learning. - Bicheng Ying; Kun Yuan 001; Stefan Vlaski; Ali H. Sayed (ITA, 2017)

Convergence of Variance-Reduced Stochastic Learning under Random Reshuffling. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (CoRR, 2017)

Efficient Variance-Reduced Learning for Fully Decentralized On-Device Intelligence. - Kun Yuan 001; Bicheng Ying; Ali H. Sayed (CoRR, 2017)

Dual Coupled Diffusion for Distributed Optimization with Affine Constraints. - Sulaiman A. Alghunaim; Kun Yuan 001; Ali H. Sayed (CDC, 2018)

An Exponentially Convergent Algorithm for Learning Under Distributed Features. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (DSW, 2018)

Efficient Variance-Reduced Learning Over Multi-Agent Networks. - Kun Yuan 001; Bicheng Ying; Ali H. Sayed (EUSIPCO, 2018)

Convergence of Variance-Reduced Learning Under Random Reshuffling. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (ICASSP, 2018)

Stochastic Learning under Random Reshuffling. - Bicheng Ying; Kun Yuan 001; Stefan Vlaski; Ali H. Sayed (CoRR, 2018)

A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. - Wotao Yin; Xianghui Mao; Kun Yuan 001; Yuantao Gu; Ali H. Sayed (CoRR, 2018)

Learning Under Distributed Features. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (CoRR, 2018)

Multi-Agent Fully Decentralized Off-Policy Learning with Linear Convergence Rates. - Lucas Cassano; Kun Yuan 001; Ali H. Sayed (CoRR, 2018)

Decentralized Consensus Optimization With Asynchrony and Delays. - Tianyu Wu; Kun Yuan 001; Qing Ling 001; Wotao Yin; Ali H. Sayed (IEEE Trans. Signal Inf. Process. over Networks, 2018)

On the Comparison between Primal and Primal-dual Methods in Decentralized Dynamic Optimization. - Wei Xu 010; Kun Yuan 001; Wotao Yin; Qing Ling 001 (ACSSC, 2019)

Decentralized Dynamic ADMM with Quantized and Censored Communications. - Yaohua Liu; Kun Yuan 001; Gang Wu 011; Zhi Tian; Qing Ling 001 (ACSSC, 2019)

On the Performance of Exact Diffusion over Adaptive Networks. - Kun Yuan 001; Sulaiman A. Alghunaim; Bicheng Ying; Ali H. Sayed (CDC, 2019)

Distributed Value-Function Learning with Linear Convergence Rates. - Lucas Cassano; Kun Yuan 001; Ali H. Sayed (ECC, 2019)

COVER: A Cluster-based Variance Reduced Method for Online Learning. - Kun Yuan 001; Bicheng Ying; Ali H. Sayed (ICASSP, 2019)

A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization. - Sulaiman A. Alghunaim; Kun Yuan 001; Ali H. Sayed (NeurIPS, 2019)

ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs. - Ernest K. Ryu; Kun Yuan 001; Wotao Yin (CoRR, 2019)

Dynamic Average Diffusion With Randomized Coordinate Updates. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Signal Inf. Process. over Networks, 2019)

Supervised Learning Under Distributed Features. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Signal Process., 2019)

Stochastic Learning Under Random Reshuffling With Constant Step-Sizes. - Bicheng Ying; Kun Yuan 001; Stefan Vlaski; Ali H. Sayed (IEEE Trans. Signal Process., 2019)

Variance-Reduced Stochastic Learning by Networked Agents Under Random Reshuffling. - Kun Yuan 001; Bicheng Ying; Jiageng Liu; Ali H. Sayed (IEEE Trans. Signal Process., 2019)

Exact Diffusion for Distributed Optimization and Learning - Part I: Algorithm Development. - Kun Yuan 001; Bicheng Ying; Xiaochuan Zhao; Ali H. Sayed (IEEE Trans. Signal Process., 2019)

Exact Diffusion for Distributed Optimization and Learning - Part II: Convergence Analysis. - Kun Yuan 001; Bicheng Ying; Xiaochuan Zhao; Ali H. Sayed (IEEE Trans. Signal Process., 2019)

A Proximal Diffusion Strategy for Multiagent Optimization With Sparse Affine Constraints. - Sulaiman A. Alghunaim; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Autom. Control., 2020)

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. - Xianghui Mao; Kun Yuan 001; Yubin Hu 001; Yuantao Gu; Ali H. Sayed; Wotao Yin (IEEE Trans. Signal Process., 2020)

Variance-Reduced Stochastic Learning Under Random Reshuffling. - Bicheng Ying; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Signal Process., 2020)

On the Influence of Bias-Correction on Distributed Stochastic Optimization. - Kun Yuan 001; Sulaiman A. Alghunaim; Bicheng Ying; Ali H. Sayed (IEEE Trans. Signal Process., 2020)

Can Primal Methods Outperform Primal-Dual Methods in Decentralized Dynamic Optimization? - Kun Yuan 001; Wei Xu 010; Qing Ling 001 (IEEE Trans. Signal Process., 2020)

DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. - Kun Yuan 001; Yiming Chen 003; Xinmeng Huang; Yingya Zhang; Pan Pan; Yinghui Xu; Wotao Yin (ICCV, 2021)

Accelerating Gossip SGD with Periodic Global Averaging. - Yiming Chen 003; Kun Yuan 001; Yingya Zhang; Pan Pan; Yinghui Xu; Wotao Yin (ICML, 2021)

An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders. - Xinmeng Huang; Kun Yuan 001; Xianghui Mao; Wotao Yin (NeurIPS, 2021)

Exponential Graph is Provably Efficient for Decentralized Deep Training. - Bicheng Ying; Kun Yuan 001; Yiming Chen 003; Hanbin Hu; Pan Pan; Wotao Yin (NeurIPS, 2021)

On the Comparison between Cyclic Sampling and Random Reshuffling. - Xinmeng Huang; Kun Yuan 001; Xianghui Mao; Wotao Yin (CoRR, 2021)

Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD. - Kun Yuan 001; Sulaiman A. Alghunaim (CoRR, 2021)

Decentralized Composite Optimization with Compression. - Yao Li; Xiaorui Liu; Jiliang Tang; Ming Yan 006; Kun Yuan 001 (CoRR, 2021)

BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning. - Bicheng Ying; Kun Yuan 001; Hanbin Hu; Yiming Chen 003; Wotao Yin (CoRR, 2021)

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates. - Sulaiman A. Alghunaim; Ernest K. Ryu; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Autom. Control., 2021)

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates. - Lucas Cassano; Kun Yuan 001; Ali H. Sayed (IEEE Trans. Autom. Control., 2021)

CHEX: CHannel EXploration for CNN Model Compression. - Zejiang Hou; Minghai Qin; Fei Sun; Xiaolong Ma; Kun Yuan 001; Yi Xu 008; Yen-Kuang Chen; Rong Jin 001; Yuan Xie 001; Sun-Yuan Kung (CVPR, 2022)

A Byzantine-Resilient Dual Subgradient Method for Vertical Federated Learning. - Kun Yuan 001; Zhaoxian Wu; Qing Ling 001 (ICASSP, 2022)

Effective Model Sparsification by Scheduled Grow-and-Prune Methods. - Xiaolong Ma; Minghai Qin; Fei Sun; Zejiang Hou; Kun Yuan 001; Yi Xu 008; Yanzhi Wang; Yen-Kuang Chen; Rong Jin 001; Yuan Xie 001 (ICLR, 2022)

Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. - Xinmeng Huang; Yiming Chen 003; Wotao Yin; Kun Yuan 001 (NeurIPS, 2022)

Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. - Zhuoqing Song; Weijian Li; Kexin Jin; Lei Shi 010; Ming Yan 006; Wotao Yin; Kun Yuan 001 (NeurIPS, 2022)

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization. - Kun Yuan 001; Xinmeng Huang; Yiming Chen 003; Xiaohan Zhang; Yingya Zhang; Pan Pan (NeurIPS, 2022)

Heavy-Tail Phenomenon in Decentralized SGD. - Mert Gürbüzbalaban; Yuanhan Hu; Umut Simsekli; Kun Yuan 001; Lingjiong Zhu (CoRR, 2022)

Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks. - Xinmeng Huang; Kun Yuan 001 (CoRR, 2022)

A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning. - Sulaiman A. Alghunaim; Kun Yuan 001 (IEEE Trans. Signal Process., 2022)

On the Performance of Gradient Tracking with Local Updates. - Edward Duc Hien Nguyen; Sulaiman A. Alghunaim; Kun Yuan 001; César A. Uribe (CDC, 2023)

Achieving Linear Speedup with Network-Independent Learning Rates in Decentralized Stochastic Optimization. - Hao Yuan; Sulaiman A. Alghunaim; Kun Yuan 001 (CDC, 2023)

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection. - Lei Yang 060; Kaicheng Yu; Tao Tang; Jun Li 082; Kun Yuan 001; Li Wang 092; Xinyu Zhang 001; Peng Chen (CVPR, 2023)

DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. - Lisang Ding; Kexin Jin; Bicheng Ying; Kun Yuan 001; Wotao Yin (ICML, 2023)

AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation. - Yifan Zhang 004; Xue Wang 010; Kexin Jin; Kun Yuan 001; Zhang Zhang 001; Liang Wang 001; Rong Jin 001; Tieniu Tan (ICML, 2023)

Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? - Yutong He; Xinmeng Huang; Kun Yuan 001 (NeurIPS, 2023)

Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression. - Yutong He; Xinmeng Huang; Yiming Chen 003; Wotao Yin; Kun Yuan 001 (CoRR, 2023)

Momentum Benefits Non-IID Federated Learning Simply and Provably. - Ziheng Cheng; Xinmeng Huang; Kun Yuan 001 (CoRR, 2023)

BEVHeight++: Toward Robust Visual Centric 3D Object Detection. - Lei Yang 060; Tao Tang; Jun Li 082; Peng Chen; Kun Yuan 001; Li Wang 092; Yi Huang; Xinyu Zhang 001; Kaicheng Yu (CoRR, 2023)

RandCom: Random Communication Skipping Method for Decentralized Stochastic Optimization. - Luyao Guo; Sulaiman A. Alghunaim; Kun Yuan 001; Laurent Condat; Jinde Cao (CoRR, 2023)

Model-free Test Time Adaptation for Out-Of-Distribution Detection. - Yifan Zhang 004; Xue Wang 010; Tian Zhou 004; Kun Yuan 001; Zhang Zhang 001; Liang Wang 001; Rong Jin 001; Tieniu Tan (CoRR, 2023)

Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD. - Kun Yuan 001; Sulaiman A. Alghunaim; Xinmeng Huang (J. Mach. Learn. Res., 2023)

Asynchronous Diffusion Learning with Agent Subsampling and Local Updates. - Elsa Rizk; Kun Yuan 001; Ali H. Sayed (ICASSP, 2024)

Momentum Benefits Non-iid Federated Learning Simply and Provably. - Ziheng Cheng; Xinmeng Huang; Pengfei Wu 006; Kun Yuan 001 (ICLR, 2024)

Distributed Bilevel Optimization with Communication Compression. - Yutong He; Jie Hu 022; Xinmeng Huang; Songtao Lu; Bin Wang; Kun Yuan 001 (ICML, 2024)

SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization. - Shuchen Zhu; Boao Kong; Songtao Lu; Xinmeng Huang; Kun Yuan 001 (NeurIPS, 2024)

Decentralized Bilevel Optimization over Graphs: Loopless Algorithmic Update and Transient Iteration Complexity. - Boao Kong; Shuchen Zhu; Songtao Lu; Xinmeng Huang; Kun Yuan 001 (CoRR, 2024)

On the Trade-off between Flatness and Optimization in Distributed Learning. - Ying Cao; Zhaoxian Wu; Kun Yuan 001; Ali H. Sayed (CoRR, 2024)

S3Attention: Improving Long Sequence Attention with Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (CoRR, 2024)

Subspace Optimization for Large Language Models with Convergence Guarantees. - Yutong He; Pengrui Li; Yipeng Hu; Chuyan Chen; Kun Yuan 001 (CoRR, 2024)

Gradient Normalization with(out) Clipping Ensures Convergence of Nonconvex SGD under Heavy-Tailed Noise with Improved Results. - Tao Sun; Xinwang Liu; Kun Yuan 001 (CoRR, 2024)

An enhanced gradient-tracking bound for distributed online stochastic convex optimization. - Sulaiman A. Alghunaim; Kun Yuan 001 (Signal Process., 2024)

S$^ text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. - Xue Wang 010; Tian Zhou 004; Jianqing Zhu; Jialin Liu 003; Kun Yuan 001; Tao Yao; Wotao Yin; Rong Jin 001; HanQin Cai (IEEE J. Sel. Top. Signal Process., 2024)

Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures. - Yiming Chen 003; Yuan Zhang; Liyuan Cao; Kun Yuan 001; Zaiwen Wen (ICLR, 2025)

Understanding the Influence of Digraphs on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm. - Liyuan Liang; Xinmeng Huang; Ran Xin; Kun Yuan 001 (SIAM J. Optim., 2025)

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models. - Guanduo Chen; Yutong He; Yipeng Hu; Kun Yuan 001; Binhang Yuan (CoRR, 2025)

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models. - Yiming Chen 003; Yuan Zhang; Yin Liu; Kun Yuan 001; Zaiwen Wen (CoRR, 2025)

Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity. - Qiankun Shi; Jie Peng; Kun Yuan 001; Xiao Wang; Qing Ling 001 (CoRR, 2025)

TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network. - Guangxin He; Yuan Cao; Yutong He; Tianyi Bai; Kun Yuan 001; Binhang Yuan (CoRR, 2025)

BEVHeight++: Toward Robust Visual Centric 3D Object Detection. - Lei Yang 060; Tao Tang; Jun Li 082; Kun Yuan 001; Kai Wu; Peng Chen; Li Wang 092; Yi Huang; Lei Li; Xinyu Zhang 001; Kaicheng Yu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)