Kun Yuan - RankMe

150 papers A* 19C 2Misc 10Journal 104Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Convergence-Motivated Learning-to-Optimize Framework for Decentralized Optimization. IEEE Trans. Signal Process. Yutong He, Qiulin Shang, Xinmeng Huang, Jialin Liu, Kun Yuan
2026	J	`jnl`	Accelerating LLM Pre-Training through Flat-Direction Dynamics Enhancement. CoRR Shuchen Zhu, Rizhen Hu, Mingze Wang, Mou Sun, Xue Wang, Kun Yuan, Zaiwen Wen
2026	J	`jnl`	Greedy Low-Rank Gradient Compression for Distributed Learning With Convergence Guarantees. IEEE Trans. Signal Process. Chuyan Chen, Yutong He, Pengrui Li, Weichen Jia, Kun Yuan
2026	J	`jnl`	Grouter: Decoupling Routing from Representation for Accelerated MoE Training. CoRR Yuqi Xu, Rizhen Hu, Zihan Liu, Mou Sun, Kun Yuan
2026	J	`jnl`	M2F: Automated Formalization of Mathematical Literature at Scale. CoRR Zichen Wang, Wanli Ma, Zhenyu Ming, Gong Zhang, Kun Yuan, Zaiwen Wen
2026	J	`jnl`	Mixture of Distributions Matters: Dynamic Sparse Attention for Efficient Video Diffusion Transformers. CoRR Yuxi Liu, Yipeng Hu, Zekun Zhang, Kunze Jiang, Kun Yuan
2026	J	`jnl`	Model-Free Test Time Adaptation for Out-of-Distribution Detection. IEEE Trans. Pattern Anal. Mach. Intell. Yifan Zhang, Xue Wang, Tian Zhou, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin
2026	J	`jnl`	Synergistic Intra- and Cross-Layer Regularization Losses for MoE Expert Specialization. CoRR Rizhen Hu, Yuan Cao, Boao Kong, Mou Sun, Kun Yuan
2025	J	`jnl`	A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models. CoRR Yiming Chen, Yuan Zhang, Yin Liu, Kun Yuan, Zaiwen Wen
2025	C	`conf`	An All-Reduce Compatible Top-$K$ Compressor for Communication-Efficient Distributed Learning. CloudCom Chuyan Chen, Chenyang Ma, Zhangxin Li, Yutong He, Yanjie Dong, Kun Yuan
2025	J	`jnl`	An All-Reduce Compatible Top-K Compressor for Communication-Efficient Distributed Learning. CoRR Chuyan Chen, Chenyang Ma, Zhangxin Li, Yutong He, Yanjie Dong, Kun Yuan
2025	J	`jnl`	BEVHeight++: Toward Robust Visual Centric 3D Object Detection. IEEE Trans. Pattern Anal. Mach. Intell. Lei Yang, Tao Tang, Jun Li, Kun Yuan, Kai Wu, Peng Chen, Li Wang, Yi Huang, Lei Li, Xinyu Zhang, Kaicheng Yu
2025	J	`jnl`	CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models. CoRR Guanduo Chen, Yutong He, Yipeng Hu, Kun Yuan, Binhang Yuan
2025	—	`conf`	D-SOBA: A Single-Loop Decentralized Bilevel Algorithm with Transient Complexity Analysis. EUSIPCO Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2025	J	`jnl`	Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity. J. Mach. Learn. Res. Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2025	J	`jnl`	Efficient Long-Context LLM Inference via KV Cache Clustering. CoRR Jie Hu, Shengnan Wang, Yutong He, Ping Gong, Jiawei Yi, Juncheng Zhang, Youhui Bai, Renhai Chen, Gong Zhang, Cheng Li, Kun Yuan
2025	A*	`conf`	Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures. ICLR Yiming Chen, Yuan Zhang, Liyuan Cao, Kun Yuan, Zaiwen Wen
2025	J	`jnl`	From PowerSGD to PowerSGD+: Low-Rank Gradient Compression for Distributed Optimization with Convergence Guarantees. CoRR Shengping Xie, Chuyan Chen, Kun Yuan
2025	C	`conf`	Greedy Low-Rank Gradient Compression Provably Converges for Distributed Learning. CloudCom Chuyan Chen, Yutong He, Pengrui Li, Weichen Jia, Yanjie Dong, Kun Yuan
2025	J	`jnl`	Greedy Low-Rank Gradient Compression for Distributed Learning with Convergence Guarantees. CoRR Chuyan Chen, Yutong He, Pengrui Li, Weichen Jia, Kun Yuan
2025	—	`conf`	HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference. ACL (Findings) Ping Gong, Jiawei Yi, Shengnan Wang, Juncheng Zhang, Zewen Jin, Ouxiang Zhou, Ruibo Liu, Guanbin Xu, Youhui Bai, Bowen Ye, Kun Yuan, Tong Yang, Gong Zhang, Renhai Chen, Feng Wu, Cheng Li
2025	J	`jnl`	HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference. CoRR Ping Gong, Jiawei Yi, Shengnan Wang, Juncheng Zhang, Zewen Jin, Ouxiang Zhou, Ruibo Liu, Guanbin Xu, Youhui Bai, Bowen Ye, Kun Yuan, Tong Yang, Gong Zhang, Renhai Chen, Feng Wu, Cheng Li
2025	J	`jnl`	MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling. CoRR Yuxi Liu, Renjia Deng, Yutong He, Xue Wang, Tao Yao, Kun Yuan
2025	J	`jnl`	MeCeFO: Enhancing LLM Training Robustness via Fault-Tolerant Optimization. CoRR Rizhen Hu, Yutong He, Ran Yan, Mou Sun, Binghang Yuan, Kun Yuan
2025	J	`jnl`	Mixture-of-Channels: Exploiting Sparse FFNs for Efficient LLMs Pre-Training and Inference. CoRR Tong Wu, Yutong He, Bin Wang, Kun Yuan
2025	J	`jnl`	On the Escaping Efficiency of Distributed Adversarial Training Algorithms. CoRR Ying Cao, Kun Yuan, Ali H. Sayed
2025	J	`jnl`	On the Trade-Off Between Flatness and Optimization in Distributed Learning. IEEE Trans. Pattern Anal. Mach. Intell. Ying Cao, Zhaoxian Wu, Kun Yuan, Ali H. Sayed
2025	J	`jnl`	Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity. CoRR Qiankun Shi, Jie Peng, Kun Yuan, Xiao Wang, Qing Ling
2025	J	`jnl`	Optimal Complexity in Byzantine-Robust Distributed Stochastic Optimization with Data Heterogeneity. J. Mach. Learn. Res. Qiankun Shi, Jie Peng, Kun Yuan, Xiao Wang, Qing Ling
2025	J	`jnl`	Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration. J. Mach. Learn. Res. Tao Sun, Xinwang Liu, Kun Yuan
2025	A*	`conf`	Subspace Optimization for Large Language Models with Convergence Guarantees. ICML Yutong He, Pengrui Li, Yipeng Hu, Chuyan Chen, Kun Yuan
2025	J	`jnl`	TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network. CoRR Guangxin He, Yuan Cao, Yutong He, Tianyi Bai, Kun Yuan, Binhang Yuan
2025	J	`jnl`	Understanding the Influence of Digraphs on Decentralized Optimization: Effective Metrics, Lower Bound, and Optimal Algorithm. SIAM J. Optim. Liyuan Liang, Xinmeng Huang, Ran Xin, Kun Yuan
2024	J	`jnl`	An enhanced gradient-tracking bound for distributed online stochastic convex optimization. Signal Process. Sulaiman A. Alghunaim, Kun Yuan
2024	Misc	`conf`	Asynchronous Diffusion Learning with Agent Subsampling and Local Updates. ICASSP Elsa Rizk, Kun Yuan, Ali H. Sayed
2024	J	`jnl`	Asynchronous Diffusion Learning with Agent Subsampling and Local Updates. CoRR Elsa Rizk, Kun Yuan, Ali H. Sayed
2024	J	`jnl`	Decentralized Bilevel Optimization over Graphs: Loopless Algorithmic Update and Transient Iteration Complexity. CoRR Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan
2024	A*	`conf`	Distributed Bilevel Optimization with Communication Compression. ICML Yutong He, Jie Hu, Xinmeng Huang, Songtao Lu, Bin Wang, Kun Yuan
2024	J	`jnl`	Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures. CoRR Yiming Chen, Yuan Zhang, Liyuan Cao, Kun Yuan, Zaiwen Wen
2024	J	`jnl`	Gradient Normalization with(out) Clipping Ensures Convergence of Nonconvex SGD under Heavy-Tailed Noise with Improved Results. CoRR Tao Sun, Xinwang Liu, Kun Yuan
2024	A*	`conf`	Momentum Benefits Non-iid Federated Learning Simply and Provably. ICLR Ziheng Cheng, Xinmeng Huang, Pengfei Wu, Kun Yuan
2024	J	`jnl`	On the Trade-off between Flatness and Optimization in Distributed Learning. CoRR Ying Cao, Zhaoxian Wu, Kun Yuan, Ali H. Sayed
2024	J	`jnl`	S CoRR Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai
2024	J	`jnl`	S$^\text{3}$Attention: Improving Long Sequence Attention With Smoothed Skeleton Sketching. IEEE J. Sel. Top. Signal Process. Xue Wang, Tian Zhou, Jianqing Zhu, Jialin Liu, Kun Yuan, Tao Yao, Wotao Yin, Rong Jin, HanQin Cai
2024	A*	`conf`	SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization. NeurIPS Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan
2024	J	`jnl`	SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization. CoRR Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan
2024	J	`jnl`	Subspace Optimization for Large Language Models with Convergence Guarantees. CoRR Yutong He, Pengrui Li, Yipeng Hu, Chuyan Chen, Kun Yuan
2023	—	`conf`	Achieving Linear Speedup with Network-Independent Learning Rates in Decentralized Stochastic Optimization. CDC Hao Yuan, Sulaiman A. Alghunaim, Kun Yuan
2023	A*	`conf`	AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation. ICML Yifan Zhang, Xue Wang, Kexin Jin, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation. CoRR Yifan Zhang, Xue Wang, Kexin Jin, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	BEVHeight++: Toward Robust Visual Centric 3D Object Detection. CoRR Lei Yang, Tao Tang, Jun Li, Peng Chen, Kun Yuan, Li Wang, Yi Huang, Xinyu Zhang, Kaicheng Yu
2023	A*	`conf`	BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection. CVPR Lei Yang, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen
2023	J	`jnl`	BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection. CoRR Lei Yang, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen
2023	A*	`conf`	DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. ICML Lisang Ding, Kexin Jin, Bicheng Ying, Kun Yuan, Wotao Yin
2023	J	`jnl`	DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm. CoRR Lisang Ding, Kexin Jin, Bicheng Ying, Kun Yuan, Wotao Yin
2023	J	`jnl`	Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression. CoRR Yutong He, Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2023	J	`jnl`	Model-free Test Time Adaptation for Out-Of-Distribution Detection. CoRR Yifan Zhang, Xue Wang, Tian Zhou, Kun Yuan, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
2023	J	`jnl`	Momentum Benefits Non-IID Federated Learning Simply and Provably. CoRR Ziheng Cheng, Xinmeng Huang, Kun Yuan
2023	—	`conf`	On the Performance of Gradient Tracking with Local Updates. CDC Edward Duc Hien Nguyen, Sulaiman A. Alghunaim, Kun Yuan, César A. Uribe
2023	J	`jnl`	RandCom: Random Communication Skipping Method for Decentralized Stochastic Optimization. CoRR Luyao Guo, Sulaiman A. Alghunaim, Kun Yuan, Laurent Condat, Jinde Cao
2023	J	`jnl`	Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD. J. Mach. Learn. Res. Kun Yuan, Sulaiman A. Alghunaim, Xinmeng Huang
2023	A*	`conf`	Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? NeurIPS Yutong He, Xinmeng Huang, Kun Yuan
2023	J	`jnl`	Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? CoRR Yutong He, Xinmeng Huang, Kun Yuan
2022	Misc	`conf`	A Byzantine-Resilient Dual Subgradient Method for Vertical Federated Learning. ICASSP Kun Yuan, Zhaoxian Wu, Qing Ling
2022	J	`jnl`	A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning. IEEE Trans. Signal Process. Sulaiman A. Alghunaim, Kun Yuan
2022	A*	`conf`	CHEX: CHannel EXploration for CNN Model Compression. CVPR Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
2022	J	`jnl`	CHEX: CHannel EXploration for CNN Model Compression. CoRR Zejiang Hou, Minghai Qin, Fei Sun, Xiaolong Ma, Kun Yuan, Yi Xu, Yen-Kuang Chen, Rong Jin, Yuan Xie, Sun-Yuan Kung
2022	A*	`conf`	Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate. NeurIPS Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
2022	J	`jnl`	Communication-Efficient Topologies for Decentralized Learning with O(1) Consensus Rate. CoRR Zhuoqing Song, Weijian Li, Kexin Jin, Lei Shi, Ming Yan, Wotao Yin, Kun Yuan
2022	A*	`conf`	Effective Model Sparsification by Scheduled Grow-and-Prune Methods. ICLR Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
2022	J	`jnl`	Heavy-Tail Phenomenon in Decentralized SGD. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Kun Yuan, Lingjiong Zhu
2022	A*	`conf`	Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. NeurIPS Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2022	J	`jnl`	Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression. CoRR Xinmeng Huang, Yiming Chen, Wotao Yin, Kun Yuan
2022	J	`jnl`	On the Performance of Gradient Tracking with Local Updates. CoRR Edward Duc Hien Nguyen, Sulaiman A. Alghunaim, Kun Yuan, César A. Uribe
2022	J	`jnl`	Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks. CoRR Xinmeng Huang, Kun Yuan
2022	A*	`conf`	Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization. NeurIPS Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan
2022	J	`jnl`	Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization. CoRR Kun Yuan, Xinmeng Huang, Yiming Chen, Xiaohan Zhang, Yingya Zhang, Pan Pan
2021	J	`jnl`	A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning. CoRR Sulaiman A. Alghunaim, Kun Yuan
2021	A*	`conf`	Accelerating Gossip SGD with Periodic Global Averaging. ICML Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021	J	`jnl`	Accelerating Gossip SGD with Periodic Global Averaging. CoRR Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021	A*	`conf`	An Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders. NeurIPS Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
2021	J	`jnl`	BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning. CoRR Bicheng Ying, Kun Yuan, Hanbin Hu, Yiming Chen, Wotao Yin
2021	A*	`conf`	DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. ICCV Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021	J	`jnl`	DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training. CoRR Kun Yuan, Yiming Chen, Xinmeng Huang, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
2021	J	`jnl`	Decentralized Composite Optimization with Compression. CoRR Yao Li, Xiaorui Liu, Jiliang Tang, Ming Yan, Kun Yuan
2021	J	`jnl`	Decentralized Proximal Gradient Algorithms With Linear Convergence Rates. IEEE Trans. Autom. Control. Sulaiman A. Alghunaim, Ernest K. Ryu, Kun Yuan, Ali H. Sayed
2021	J	`jnl`	Effective Model Sparsification by Scheduled Grow-and-Prune Methods. CoRR Xiaolong Ma, Minghai Qin, Fei Sun, Zejiang Hou, Kun Yuan, Yi Xu, Yanzhi Wang, Yen-Kuang Chen, Rong Jin, Yuan Xie
2021	A*	`conf`	Exponential Graph is Provably Efficient for Decentralized Deep Training. NeurIPS Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
2021	J	`jnl`	Exponential Graph is Provably Efficient for Decentralized Deep Training. CoRR Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
2021	J	`jnl`	Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates. IEEE Trans. Autom. Control. Lucas Cassano, Kun Yuan, Ali H. Sayed
2021	J	`jnl`	On the Comparison between Cyclic Sampling and Random Reshuffling. CoRR Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
2021	J	`jnl`	Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD. CoRR Kun Yuan, Sulaiman A. Alghunaim
2020	J	`jnl`	A Proximal Diffusion Strategy for Multiagent Optimization With Sparse Affine Constraints. IEEE Trans. Autom. Control. Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
2020	J	`jnl`	Can Primal Methods Outperform Primal-Dual Methods in Decentralized Dynamic Optimization? IEEE Trans. Signal Process. Kun Yuan, Wei Xu, Qing Ling
2020	J	`jnl`	On the Influence of Bias-Correction on Distributed Stochastic Optimization. IEEE Trans. Signal Process. Kun Yuan, Sulaiman A. Alghunaim, Bicheng Ying, Ali H. Sayed
2020	J	`jnl`	Variance-Reduced Stochastic Learning Under Random Reshuffling. IEEE Trans. Signal Process. Bicheng Ying, Kun Yuan, Ali H. Sayed
2020	J	`jnl`	Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. IEEE Trans. Signal Process. Xianghui Mao, Kun Yuan, Yubin Hu, Yuantao Gu, Ali H. Sayed, Wotao Yin
2019	A*	`conf`	A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization. NeurIPS Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
2019	J	`jnl`	A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization. CoRR Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
2019	Misc	`conf`	COVER: A Cluster-based Variance Reduced Method for Online Learning. ICASSP Kun Yuan, Bicheng Ying, Ali H. Sayed
2019	Misc	`conf`	Decentralized Dynamic ADMM with Quantized and Censored Communications. ACSSC Yaohua Liu, Kun Yuan, Gang Wu, Zhi Tian, Qing Ling
2019	—	`conf`	Distributed Value-Function Learning with Linear Convergence Rates. ECC Lucas Cassano, Kun Yuan, Ali H. Sayed
2019	J	`jnl`	Dynamic Average Diffusion With Randomized Coordinate Updates. IEEE Trans. Signal Inf. Process. over Networks Bicheng Ying, Kun Yuan, Ali H. Sayed
2019	J	`jnl`	Exact Diffusion for Distributed Optimization and Learning - Part I: Algorithm Development. IEEE Trans. Signal Process. Kun Yuan, Bicheng Ying, Xiaochuan Zhao, Ali H. Sayed
2019	J	`jnl`	Exact Diffusion for Distributed Optimization and Learning - Part II: Convergence Analysis. IEEE Trans. Signal Process. Kun Yuan, Bicheng Ying, Xiaochuan Zhao, Ali H. Sayed
2019	J	`jnl`	ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems and GANs. CoRR Ernest K. Ryu, Kun Yuan, Wotao Yin
2019	Misc	`conf`	On the Comparison between Primal and Primal-dual Methods in Decentralized Dynamic Optimization. ACSSC Wei Xu, Kun Yuan, Wotao Yin, Qing Ling
2019	—	`conf`	On the Performance of Exact Diffusion over Adaptive Networks. CDC Kun Yuan, Sulaiman A. Alghunaim, Bicheng Ying, Ali H. Sayed
2019	J	`jnl`	On the Performance of Exact Diffusion over Adaptive Networks. CoRR Kun Yuan, Sulaiman A. Alghunaim, Bicheng Ying, Ali H. Sayed
2019	J	`jnl`	Stochastic Learning Under Random Reshuffling With Constant Step-Sizes. IEEE Trans. Signal Process. Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
2019	J	`jnl`	Supervised Learning Under Distributed Features. IEEE Trans. Signal Process. Bicheng Ying, Kun Yuan, Ali H. Sayed
2019	J	`jnl`	Variance-Reduced Stochastic Learning by Networked Agents Under Random Reshuffling. IEEE Trans. Signal Process. Kun Yuan, Bicheng Ying, Jiageng Liu, Ali H. Sayed
2018	J	`jnl`	A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization. CoRR Wotao Yin, Xianghui Mao, Kun Yuan, Yuantao Gu, Ali H. Sayed
2018	—	`conf`	An Exponentially Convergent Algorithm for Learning Under Distributed Features. DSW Bicheng Ying, Kun Yuan, Ali H. Sayed
2018	Misc	`conf`	Convergence of Variance-Reduced Learning Under Random Reshuffling. ICASSP Bicheng Ying, Kun Yuan, Ali H. Sayed
2018	J	`jnl`	Decentralized Consensus Optimization With Asynchrony and Delays. IEEE Trans. Signal Inf. Process. over Networks Tianyu Wu, Kun Yuan, Qing Ling, Wotao Yin, Ali H. Sayed
2018	—	`conf`	Dual Coupled Diffusion for Distributed Optimization with Affine Constraints. CDC Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
2018	J	`jnl`	Dynamic Average Diffusion with randomized Coordinate Updates. CoRR Bicheng Ying, Kun Yuan, Ali H. Sayed
2018	—	`conf`	Efficient Variance-Reduced Learning Over Multi-Agent Networks. EUSIPCO Kun Yuan, Bicheng Ying, Ali H. Sayed
2018	J	`jnl`	Learning Under Distributed Features. CoRR Bicheng Ying, Kun Yuan, Ali H. Sayed
2018	J	`jnl`	Multi-Agent Fully Decentralized Off-Policy Learning with Linear Convergence Rates. CoRR Lucas Cassano, Kun Yuan, Ali H. Sayed
2018	J	`jnl`	Stochastic Learning under Random Reshuffling. CoRR Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
2017	J	`jnl`	Convergence of Variance-Reduced Stochastic Learning under Random Reshuffling. CoRR Bicheng Ying, Kun Yuan, Ali H. Sayed
2017	—	`conf`	Decentralized exact coupled optimization. Allerton Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
2017	J	`jnl`	Efficient Variance-Reduced Learning for Fully Decentralized On-Device Intelligence. CoRR Kun Yuan, Bicheng Ying, Ali H. Sayed
2017	—	`conf`	Exact diffusion strategy for optimization by networked agents. EUSIPCO Kun Yuan, Bicheng Ying, Xiaochuan Zhao, Ali H. Sayed
2017	Misc	`conf`	On the performance of random reshuffling in stochastic learning. ITA Bicheng Ying, Kun Yuan, Stefan Vlaski, Ali H. Sayed
2016	J	`jnl`	Cooperative tracking for nonlinear multi-agent systems with hybrid time-delayed protocol. Neurocomputing Jian-Qiang Hu, Jinde Cao, Kun Yuan, Tasawar Hayat
2016	J	`jnl`	Decentralized Consensus Optimization with Asynchrony and Delays. CoRR Tianyu Wu, Kun Yuan, Qing Ling, Wotao Yin, Ali H. Sayed
2016	Misc	`conf`	Decentralized consensus optimization with asynchrony and delays. ACSSC Tianyu Wu, Kun Yuan, Qing Ling, Wotao Yin, Ali H. Sayed
2016	J	`jnl`	On the Convergence of Decentralized Gradient Descent. SIAM J. Optim. Kun Yuan, Qing Ling, Wotao Yin
2016	J	`jnl`	On the Influence of Momentum Acceleration on Online Learning. CoRR Kun Yuan, Bicheng Ying, Ali H. Sayed
2016	J	`jnl`	On the Influence of Momentum Acceleration on Online Learning. J. Mach. Learn. Res. Kun Yuan, Bicheng Ying, Ali H. Sayed
2016	Misc	`conf`	On the influence of momentum acceleration on online learning. ICASSP Kun Yuan, Bicheng Ying, Ali H. Sayed
2016	J	`jnl`	Online Dual Coordinate Ascent Learning. CoRR Bicheng Ying, Kun Yuan, Ali H. Sayed
2016	—	`conf`	Online dual coordinate ascent learning. EUSIPCO Bicheng Ying, Kun Yuan, Ali H. Sayed
2016	—	`conf`	Stochastic gradient descent with finite samples sizes. MLSP Kun Yuan, Bicheng Ying, Stefan Vlaski, Ali H. Sayed
2015	J	`jnl`	A decentralised linear programming approach to energy-efficient event detection. Int. J. Sens. Networks Kun Yuan, Qing Ling, Zhi Tian
2015	J	`jnl`	Communication-Efficient Decentralized Event Monitoring in Wireless Sensor Networks. IEEE Trans. Parallel Distributed Syst. Kun Yuan, Qing Ling, Zhi Tian
2014	J	`jnl`	On the Linear Convergence of the ADMM in Decentralized Consensus Optimization. IEEE Trans. Signal Process. Wei Shi, Qing Ling, Kun Yuan, Gang Wu, Wotao Yin
2014	J	`jnl`	Partial synchronization of the distributed parameter system with time delay via fuzzy control. IMA J. Math. Control. Inf. Kun Yuan, Shumin Fei, Jinde Cao
2013	—	`conf`	A linearized bregman algorithm for decentralized basis pursuit. EUSIPCO Kun Yuan, Qing Ling, Wotao Yin, Alejandro Ribeiro
2013	Misc	`conf`	Linearly convergent decentralized consensus optimization with the alternating direction method of multipliers. ICASSP Wei Shi, Qing Ling, Kun Yuan, Gang Wu, Wotao Yin
2012	J	`jnl`	Synchronization of Coupled Networks with Mixed Delays by Intermittent Control. J. Appl. Math. Kun Yuan, Jinde Cao, Shumin Fei
2008	J	`jnl`	Robust Stabilization of the Distributed Parameter System With Time Delay via Fuzzy Control. IEEE Trans. Fuzzy Syst. Kun Yuan, Han-Xiong Li, Jinde Cao
2006	J	`jnl`	Exponential stability and periodic solutions of fuzzy cellular neural networks with time-varying delays. Neurocomputing Kun Yuan, Jinde Cao, Jianming Deng
2006	J	`jnl`	Global Asymptotical Stability of Recurrent Neural Networks With Multiple Discrete Delays and Distributed Delays. IEEE Trans. Neural Networks Jinde Cao, Kun Yuan, Han-Xiong Li
2006	J	`jnl`	Robust Stability of Switched Cohen-Grossberg Neural Networks With Mixed Time-Varying Delays. IEEE Trans. Syst. Man Cybern. Part B Kun Yuan, Jinde Cao, Han-Xiong Li
2005	J	`jnl`	An analysis of global asymptotic stability of delayed Cohen-Grossberg neural networks via nonsmooth analysis. IEEE Trans. Circuits Syst. I Regul. Pap. Kun Yuan, Jinde Cao
2004	—	`conf`	Global Exponential Stability of Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays. ISNN (1) Kun Yuan, Jinde Cao