A New Local Density for Density Peak Clustering. - Zhishuai Guo; Tianyi Huang; Zhiling Cai; William Zhu 001 (PAKDD (3), 2018)

Accelerating Deep Learning with Millions of Classes. - Zhuoning Yuan; Zhishuai Guo; Xiaotian Yu; Xiaoyu Wang 002; Tianbao Yang (ECCV (23), 2020)

Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks. - Zhishuai Guo; Mingrui Liu; Zhuoning Yuan; Li Shen 005; Wei Liu 005; Tianbao Yang (ICML, 2020)

Revisiting SGD with Increasingly Weighted Averaging: Optimization and Generalization Perspectives. - Zhishuai Guo; Zixuan Wu; Yan Yan 006; Xiaoyu Wang 002; Tianbao Yang (CoRR, 2020)

Fast Objective and Duality Gap Convergence for Non-convex Strongly-concave Min-max Problems. - Zhishuai Guo; Zhuoning Yuan; Yan Yan 006; Tianbao Yang (CoRR, 2020)

A Practical Online Method for Distributionally Deep Robust Optimization. - Qi Qi 006; Zhishuai Guo; Yi Xu 008; Rong Jin 001; Tianbao Yang (CoRR, 2020)

Research on Cultivation of Innovation and Entrepreneurship Ability of Applied Talents under the Concept of "New Engineering". - Jing Gao; Zhishuai Guo; Yong Xiao (CIPAE, 2021)

Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity. - Zhuoning Yuan; Zhishuai Guo; Yi Xu 008; Yiming Ying; Tianbao Yang (ICML, 2021)

An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives. - Qi Qi 006; Zhishuai Guo; Yi Xu 008; Rong Jin 001; Tianbao Yang (NeurIPS, 2021)

Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity. - Zhuoning Yuan; Zhishuai Guo; Yi Xu 008; Yiming Ying; Tianbao Yang (CoRR, 2021)

On Stochastic Moving-Average Estimators for Non-Convex Optimization. - Zhishuai Guo; Yi Xu 008; Wotao Yin; Rong Jin 001; Tianbao Yang (CoRR, 2021)

Randomized Stochastic Variance-Reduced Methods for Stochastic Bilevel Optimization. - Zhishuai Guo; Tianbao Yang (CoRR, 2021)

A Novel Convergence Analysis for Algorithms of the Adam Family. - Zhishuai Guo; Yi Xu 008; Wotao Yin; Rong Jin 001; Tianbao Yang (CoRR, 2021)

Compositional Training for End-to-End Deep AUC Maximization. - Zhuoning Yuan; Zhishuai Guo; Nitesh V. Chawla; Tianbao Yang (ICLR, 2022)

FedX: Federated Learning for Compositional Pairwise Risk Optimization. - Zhishuai Guo; Rong Jin 001; Jiebo Luo 001; Tianbao Yang (CoRR, 2022)

FeDXL: Provable Federated Learning for Deep X-Risk Optimization. - Zhishuai Guo; Rong Jin 001; Jiebo Luo 001; Tianbao Yang (ICML, 2023)

Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization. - Quanqi Hu; Zi-Hao Qiu; Zhishuai Guo; Lijun Zhang 005; Tianbao Yang (ICML, 2023)

Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition. - Zhishuai Guo; Yan Yan 006; Zhuoning Yuan; Tianbao Yang (J. Mach. Learn. Res., 2023)

Communication-Efficient Federated Group Distributionally Robust Optimization. - Zhishuai Guo; Tianbao Yang (NeurIPS, 2024)

Generating empathetic responses through emotion tracking and constraint guidance. - Jing Li; Donghong Han; Zhishuai Guo; Baiyou Qiao; Gang Wu 007 (Frontiers Comput. Sci., 2024)

FutureGen: LLM-RAG Approach to Generate the Future Work of Scientific Article. - Ibrahim Al Azher; Miftahul Jannat Mokarrama; Zhishuai Guo; Sagnik Ray Choudhury; Hamed Alhoori (CoRR, 2025)

BAGELS: Benchmarking the Automated Generation and Extraction of Limitations from Scholarly Text. - Ibrahim Al Azher; Miftahul Jannat Mokarrama; Zhishuai Guo; Sagnik Ray Choudhury; Hamed Alhoori (CoRR, 2025)

Frequency-Semantic Enhanced Variational Autoencoder for Zero-Shot Skeleton-based Action Recognition. - Wenhan Wu; Zhishuai Guo; Chen Chen 001; Hongfei Xue; Aidong Lu (CoRR, 2025)