Zhize Li
21 papers · 2015–2025 · 8 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (26) π Conference Polyglot Β· Silver π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π¬
Deep Specialist
(15)
π
Grand Slam
π
Keyword Champion
(2)
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
ποΈ
Keyword Collector
(74)
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(21)
Optimization & Theory Β· Machine Learning
(18)
Artificial Intelligence
(8)
Mathematics & Optimization
(8)
Learning Paradigms Β· Artificial Intelligence
(8)
Optimization
(8)
Deep Learning
(6)
Learning Paradigms Β· Machine Learning
(5)
Optimization & Theory Β· Deep Learning
(4)
Core Methods
(3)
Application Areas
(2)
Learning Types Β· Deep Learning
(2)
Learning Types Β· Machine Learning
(2)
Computer Science
(1)
Security & Privacy
(1)
Keywords
non-convex optimization
(8)
federated learning
(7)
distributed optimization
(7)
communication compression
(7)
variance reduction
(6)
stochastic gradient descent
(5)
error feedback
(4)
stochastic gradient
(4)
gradient descent
(4)
convex optimization
(3)
gradient estimator
(2)
finite-sum optimization
(2)
saddle point
(2)
optimal convergence rate
(2)
proximal gradient
(2)
linear convergence
(2)
convergence rate
(2)
accelerated gradient
(2)
nonsmooth optimization
(2)
second-order stationary point
(2)
Papers
EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback
JMLR 2025
EFSkip: A New Error Feedback with Linear Speedup for Compressed Federated Learning with Arbitrary Data Heterogeneity
AAAI 2025
SIFAR: A Simple Faster Accelerated Variance-Reduced Gradient Method
IJCAI 2025
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression
AISTATS 2024
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation
ICML 2022
BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression
NeurIPS 2022
Coresets for Vertical Federated Learning: Regularized Linear Regression and K-Means Clustering
NeurIPS 2022
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization
JMLR 2022
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression
NeurIPS 2022
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression
NeurIPS 2021
MARINA: Faster Non-Convex Distributed Learning with Compression
ICML 2021
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
ICML 2021
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
ICML 2020
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization
AISTATS 2020
A unified variance-reduced accelerated gradient method for convex optimization
NeurIPS 2019
Gradient Boosting with Piece-Wise Linear Regression Trees
IJCAI 2019
Learning Two-layer Neural Networks with Symmetric Inputs
ICLR 2019
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
NeurIPS 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
COLT 2019
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization
NeurIPS 2018
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs
NeurIPS 2015