Zhishuai Guo

According to our database1, Zhishuai Guo authored at least 19 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Generating empathetic responses through emotion tracking and constraint guidance.
Frontiers Comput. Sci., April, 2024

2023
Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition.
J. Mach. Learn. Res., 2023

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization.
Proceedings of the International Conference on Machine Learning, 2023

FeDXL: Provable Federated Learning for Deep X-Risk Optimization.
Proceedings of the International Conference on Machine Learning, 2023

2022
FedX: Federated Learning for Compositional Pairwise Risk Optimization.
CoRR, 2022

Compositional Training for End-to-End Deep AUC Maximization.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
A Novel Convergence Analysis for Algorithms of the Adam Family.
CoRR, 2021

Randomized Stochastic Variance-Reduced Methods for Stochastic Bilevel Optimization.
CoRR, 2021

On Stochastic Moving-Average Estimators for Non-Convex Optimization.
CoRR, 2021

Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity.
CoRR, 2021

An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity.
Proceedings of the 38th International Conference on Machine Learning, 2021

Research on Cultivation of Innovation and Entrepreneurship Ability of Applied Talents under the Concept of "New Engineering".
Proceedings of the CIPAE 2021: 2nd International Conference on Computers, 2021

2020
A Practical Online Method for Distributionally Deep Robust Optimization.
CoRR, 2020

Fast Objective and Duality Gap Convergence for Non-convex Strongly-concave Min-max Problems.
CoRR, 2020

Revisiting SGD with Increasingly Weighted Averaging: Optimization and Generalization Perspectives.
CoRR, 2020

Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Accelerating Deep Learning with Millions of Classes.
Proceedings of the Computer Vision - ECCV 2020, 2020

2018
A New Local Density for Density Peak Clustering.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018


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