Zhize Li

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 53

Top Topics

Variance Reduction

Algorithm For Linear Programming

Top Venues

SIAM J. Math. Data Sci.

Publications

Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
Faster Rates for Compressed Federated Learning with Client-Variance Reduction. SIAM J. Math. Data Sci. 6 (1) (2024)
Sijin Chen, Zhize Li, Yuejie Chi
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. AISTATS (2024)
Sijin Chen, Zhize Li, Yuejie Chi
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression. CoRR (2023)
Zhize Li, Jian Li, Hongwei Huo
Optimal in-place suffix sorting. Inf. Comput. 285 (Part) (2022)
Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression. NeurIPS (2022)
Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. CoRR (2022)
Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao
Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering. NeurIPS (2022)
Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin, Elnur Gasanov, Zhize Li, Eduard A. Gorbunov
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation. CoRR (2022)
Boyue Li, Zhize Li, Yuejie Chi
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. SIAM J. Math. Data Sci. 4 (3) (2022)
Zhize Li, Haoyu Zhao, Boyue Li, Yuejie Chi
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression. NeurIPS (2022)
Haoyu Zhao, Boyue Li, Zhize Li, Peter Richtárik, Yuejie Chi
BEER: Fast O(1/T) Rate for Decentralized Nonconvex Optimization with Communication Compression. CoRR (2022)
Zhize Li, Jian Li
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization. J. Mach. Learn. Res. 23 (2022)
Zhize Li, Jian Li
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization. CoRR (2022)
Peter Richtárik, Igor Sokolov, Elnur Gasanov, Ilyas Fatkhullin, Zhize Li, Eduard Gorbunov
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation. ICML (2022)
Lingxiao Huang, Zhize Li, Jialin Sun, Haoyu Zhao
Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering. CoRR (2022)
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtárik
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization. ICML (2021)
Zhize Li, Peter Richtárik
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression. NeurIPS (2021)
Eduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
MARINA: Faster Non-Convex Distributed Learning with Compression. CoRR (2021)
Haoyu Zhao, Konstantin Burlachenko, Zhize Li, Peter Richtárik
Faster Rates for Compressed Federated Learning with Client-Variance Reduction. CoRR (2021)
Zhize Li, Peter Richtárik
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression. CoRR (2021)
Zhize Li, Peter Richtárik
ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation. CoRR (2021)
Zhize Li
A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization. CoRR (2021)
Boyue Li, Zhize Li, Yuejie Chi
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization. CoRR (2021)
Eduard A. Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtárik
MARINA: Faster Non-Convex Distributed Learning with Compression. ICML (2021)
Zhize Li
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method. CoRR (2021)
Ilyas Fatkhullin, Igor Sokolov, Eduard A. Gorbunov, Zhize Li, Peter Richtárik
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback. CoRR (2021)
Haoyu Zhao, Zhize Li, Peter Richtárik
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning. CoRR (2021)
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. ICML (2020)
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtárik
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization. CoRR (2020)
Zhize Li, Peter Richtárik
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization. CoRR (2020)
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtárik
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization. CoRR (2020)
Zhize Li, Jian Li
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization. AISTATS (2020)
Guanghui Lan, Zhize Li, Yi Zhou
A unified variance-reduced accelerated gradient method for convex optimization. CoRR (2019)
Guanghui Lan, Zhize Li, Yi Zhou
A unified variance-reduced accelerated gradient method for convex optimization. NeurIPS (2019)
Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
Learning Two-layer Neural Networks with Symmetric Inputs. ICLR (Poster) (2019)
Zhize Li, Tianyi Zhang, Shuyu Cheng, Jun Zhu, Jian Li
Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference. Mach. Learn. 108 (8-9) (2019)
Zhize Li
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points. CoRR (2019)
Yu Shi, Jian Li, Zhize Li
Gradient Boosting with Piece-Wise Linear Regression Trees. IJCAI (2019)
Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. CoRR (2019)
Zhize Li
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points. NeurIPS (2019)
Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. COLT (2019)
Zhize Li, Le Zhang, Zhixuan Fang, Jian Li
A Two-Stage Mechanism for Ordinal Peer Assessment. SAGT (2018)
Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang
Learning Two-layer Neural Networks with Symmetric Inputs. CoRR (2018)
Zhize Li, Jian Li, Hongwei Huo
Optimal In-Place Suffix Sorting. DCC (2018)
Zhize Li, Jian Li
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization. CoRR (2018)
Yu Shi, Jian Li, Zhize Li
Gradient Boosting With Piece-Wise Linear Regression Trees. CoRR (2018)
Zhize Li, Wei Zhang, Kees Roos
A Fast Polynomial-time Primal-Dual Projection Algorithm for Linear Programming. CoRR (2018)
Zhize Li, Jian Li
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization. NeurIPS (2018)
Zhize Li, Jian Li
An Anderson-Chebyshev Mixing Method for Nonlinear Optimization. CoRR (2018)
Zhize Li, Jian Li, Hongwei Huo
Optimal In-Place Suffix Sorting. SPIRE (2018)
Zhize Li, Tianyi Zhang, Jian Li
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference. CoRR (2018)
Zengyin Yang, Qian Wu, Zhize Li, Hewu Li, Jianping Wu
Modeling and Routing for Predictable Dynamic Networks. CoRR (2017)
Zhize Li, Jian Li, Hongwei Huo
Optimal In-Place Suffix Sorting. CoRR (2016)
Wei Cao, Jian Li, Yufei Tao, Zhize Li
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs. NIPS (2015)