Zhize Li

According to our database1, Zhize Li authored at least 33 papers between 2015 and 2024.

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Bibliography

2024
Faster Rates for Compressed Federated Learning with Client-Variance Reduction.
SIAM J. Math. Data Sci., March, 2024

Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2022
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization.
SIAM J. Math. Data Sci., 2022

Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization.
J. Mach. Learn. Res., 2022

Optimal in-place suffix sorting.
Inf. Comput., 2022

BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Coresets for Vertical Federated Learning: Regularized Linear Regression and $K$-Means Clustering.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation.
Proceedings of the International Conference on Machine Learning, 2022

2021
EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback.
CoRR, 2021

FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning.
CoRR, 2021

A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization.
CoRR, 2021

ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method.
CoRR, 2021

ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation.
CoRR, 2021

CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization.
Proceedings of the 38th International Conference on Machine Learning, 2021

MARINA: Faster Non-Convex Distributed Learning with Compression.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization.
CoRR, 2020

Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Stochastic gradient Hamiltonian Monte Carlo with variance reduction for Bayesian inference.
Mach. Learn., 2019

SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A unified variance-reduced accelerated gradient method for convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Gradient Boosting with Piece-Wise Linear Regression Trees.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Learning Two-layer Neural Networks with Symmetric Inputs.
Proceedings of the 7th International Conference on Learning Representations, 2019

Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization.
Proceedings of the Conference on Learning Theory, 2019

2018
A Fast Polynomial-time Primal-Dual Projection Algorithm for Linear Programming.
CoRR, 2018

An Anderson-Chebyshev Mixing Method for Nonlinear Optimization.
CoRR, 2018

Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference.
CoRR, 2018

A Two-Stage Mechanism for Ordinal Peer Assessment.
Proceedings of the Algorithmic Game Theory - 11th International Symposium, 2018

A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Modeling and Routing for Predictable Dynamic Networks.
CoRR, 2017

2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015


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