Zhize Li - RankMe

63 papers A* 16A 2B 2C 1Journal 40Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Coresets for Clustering Under Stochastic Noise. CoRR Lingxiao Huang, Zhize Li, Nisheeth K. Vishnoi, Runkai Yang, Haoyu Zhao
2025	J	`jnl`	EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback. J. Mach. Learn. Res. Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov, Zhize Li, Peter Richtárik
2025	A*	`conf`	EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity. AAAI Hongyan Bao, Pengwen Chen, Ying Sun, Zhize Li
2025	A*	`conf`	From Risk to Resilience: Towards Assessing and Mitigating the Risk of Data Reconstruction Attacks in Federated Learning. USENIX Security Symposium Xiangrui Xu, Zhize Li, Yufei Han, Bin Wang, Jiqiang Liu, Wei Wang
2025	J	`jnl`	From Risk to Resilience: Towards Assessing and Mitigating the Risk of Data Reconstruction Attacks in Federated Learning. CoRR Xiangrui Xu, Zhize Li, Yufei Han, Bin Wang, Jiqiang Liu, Wei Wang
2025	J	`jnl`	On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective. CoRR Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Yujun Zhou, Yanbo Wang, Jiayi Ye, Jiawen Shi, Qihui Zhang, Yuan Li, Han Bao, Zhaoyi Liu, Tianrui Guan, Dongping Chen, Ruoxi Chen, Kehan Guo, Andy Zou, Bryan Hooi Kuen-Yew, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jaehong Yoon, Jieyu Zhang, Kai Shu, Kaijie Zhu, Ranjay Krishna, Swabha Swayamdipta, Taiwei Shi, Weijia Shi, Xiang Li, Yiwei Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V. Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Xiangliang Zhang
2025	A*	`conf`	SIFAR: A Simple Faster Accelerated Variance-Reduced Gradient Method. IJCAI Zhize Li
2025	J	`jnl`	The Effectiveness of Local Updates for Decentralized Learning Under Data Heterogeneity. IEEE Trans. Signal Process. Tongle Wu, Zhize Li, Ying Sun
2025	J	`jnl`	X-VFL: A New Vertical Federated Learning Framework with Cross Completion and Decision Subspace Alignment. CoRR Qinghua Yao, Xiangrui Xu, Zhize Li
2024	A	`conf`	Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. AISTATS Sijin Chen, Zhize Li, Yuejie Chi
2024	J	`jnl`	Faster Rates for Compressed Federated Learning with Client-Variance Reduction. SIAM J. Math. Data Sci. Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
2023	J	`jnl`	Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. CoRR Sijin Chen, Zhize Li, Yuejie Chi
2022	A*	`conf`	3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation. ICML Peter Richtárik, Igor Sokolov, Elnur Gasanov, Ilyas Fatkhullin, Zhize Li, Eduard Gorbunov
2022	J	`jnl`	3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation. CoRR Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin, Elnur Gasanov, Zhize Li, Eduard Gorbunov
2022	A*	`conf`	BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression. NeurIPS Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi
2022	J	`jnl`	BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression. CoRR Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi
2022	A*	`conf`	Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering. NeurIPS Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao
2022	J	`jnl`	Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering. CoRR Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao
2022	J	`jnl`	DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. SIAM J. Math. Data Sci. Boyue Li, Zhize Li, Yuejie Chi
2022	J	`jnl`	Optimal in-place suffix sorting. Inf. Comput. Zhize Li, Jian Li, Hongwei Huo
2022	J	`jnl`	Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization. CoRR Zhize Li, Jian Li
2022	J	`jnl`	Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization. J. Mach. Learn. Res. Zhize Li, Jian Li
2022	A*	`conf`	SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. NeurIPS Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
2022	J	`jnl`	SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. CoRR Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
2021	J	`jnl`	A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization. CoRR Zhize Li
2021	J	`jnl`	ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method. CoRR Zhize Li
2021	A*	`conf`	CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression. NeurIPS Zhize Li, Peter Richtárik
2021	J	`jnl`	CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression. CoRR Zhize Li, Peter Richtárik
2021	J	`jnl`	DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. CoRR Boyue Li, Zhize Li, Yuejie Chi
2021	J	`jnl`	EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback. CoRR Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov, Zhize Li, Peter Richtárik
2021	J	`jnl`	Faster Rates for Compressed Federated Learning with Client-Variance Reduction. CoRR Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
2021	J	`jnl`	FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning. CoRR Haoyu Zhao, Zhize Li, Peter Richtárik
2021	A*	`conf`	MARINA: Faster Non-Convex Distributed Learning with Compression. ICML Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
2021	J	`jnl`	MARINA: Faster Non-Convex Distributed Learning with Compression. CoRR Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
2021	A*	`conf`	PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization. ICML Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtárik
2021	J	`jnl`	ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation. CoRR Zhize Li, Peter Richtárik
2020	A	`conf`	A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization. AISTATS Zhize Li, Jian Li
2020	J	`jnl`	A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization. CoRR Zhize Li, Peter Richtárik
2020	A*	`conf`	Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. ICML Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
2020	J	`jnl`	Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. CoRR Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
2020	J	`jnl`	PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization. CoRR Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtárik
2019	A*	`conf`	A unified variance-reduced accelerated gradient method for convex optimization. NeurIPS Guanghui Lan, Zhize Li, Yi Zhou
2019	J	`jnl`	A unified variance-reduced accelerated gradient method for convex optimization. CoRR Guanghui Lan, Zhize Li, Yi Zhou
2019	A*	`conf`	Gradient Boosting with Piece-Wise Linear Regression Trees. IJCAI Yu Shi, Jian Li, Zhize Li
2019	—	`conf`	Learning Two-layer Neural Networks with Symmetric Inputs. ICLR (Poster) Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
2019	A*	`conf`	SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points. NeurIPS Zhize Li
2019	J	`jnl`	SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points. CoRR Zhize Li
2019	A*	`conf`	Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. COLT Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
2019	J	`jnl`	Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. CoRR Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
2019	J	`jnl`	Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference. Mach. Learn. Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li
2018	J	`jnl`	A Fast Polynomial-time Primal-Dual Projection Algorithm for Linear Programming. CoRR Zhize Li, Wei Zhang, Kees Roos
2018	A*	`conf`	A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization. NeurIPS Zhize Li, Jian Li
2018	J	`jnl`	A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization. CoRR Zhize Li, Jian Li
2018	B	`conf`	A Two-Stage Mechanism for Ordinal Peer Assessment. SAGT Zhize Li, Le Zhang, Zhixuan Fang, Jian Li
2018	J	`jnl`	An Anderson-Chebyshev Mixing Method for Nonlinear Optimization. CoRR Zhize Li, Jian Li
2018	J	`jnl`	Gradient Boosting With Piece-Wise Linear Regression Trees. CoRR Yu Shi, Jian Li, Zhize Li
2018	J	`jnl`	Learning Two-layer Neural Networks with Symmetric Inputs. CoRR Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
2018	B	`conf`	Optimal In-Place Suffix Sorting. DCC Zhize Li, Jian Li, Hongwei Huo
2018	C	`conf`	Optimal In-Place Suffix Sorting. SPIRE Zhize Li, Jian Li, Hongwei Huo
2018	J	`jnl`	Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference. CoRR Zhize Li, Tianyi Zhang, Jian Li
2017	J	`jnl`	Modeling and Routing for Predictable Dynamic Networks. CoRR Zengyin Yang, Qian Wu, Zhize Li, Hewu Li, Jianping Wu
2016	J	`jnl`	Optimal In-Place Suffix Sorting. CoRR Zhize Li, Jian Li, Hongwei Huo
2015	—	`conf`	On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs. NIPS Wei Cao, Jian Li, Yufei Tao, Zhize Li