Zhishuai Guo
11 papers · 2020–2025 · 7 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 ↓+3 more ↓ Show less ↑
π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (18) π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory Β· Machine Learning
(7)
Deep Learning
(3)
Mathematics & Optimization
(3)
Optimization
(3)
Core Methods
(2)
Learning Paradigms
(2)
Learning Types
(2)
Optimization & Theory Β· Deep Learning
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Healthcare & Medicine
(1)
Natural Language Processing
(1)
Analysis
(1)
Applications
(1)
Keywords
federated learning
(3)
stochastic optimization
(3)
non-convex optimization
(3)
auc maximization
(2)
communication efficiency
(2)
min-max optimization
(2)
imbalanced classification
(2)
kl regularization
(1)
kullback-leibler divergence
(1)
text classification
(1)
semantic representation
(1)
variance reduction
(1)
distributed learning
(1)
neural network training
(1)
distributionally robust optimization
(1)
communication complexity
(1)
bilevel optimization
(1)
convergence rate
(1)
deep neural network
(1)
parallel speedup
(1)
Papers
BAGELS: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text
EMNLP 2025
Frequency-Semantic Enhanced Variational Autoencoder for Zero-Shot Skeleton-based Action Recognition
ICCV 2025
Communication-Efficient Federated Group Distributionally Robust Optimization
NeurIPS 2024
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization
ICML 2023
Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition
JMLR 2023
FeDXL: Provable Federated Learning for Deep X-Risk Optimization
ICML 2023
Compositional Training for End-to-End Deep AUC Maximization
ICLR 2022
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives
NeurIPS 2021
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
ICML 2021
Accelerating Deep Learning with Millions of Classes
ECCV 2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
ICML 2020