| 2025 | AIME | FSLearning: An Efficient Federated Split Learning Framework for Privacy-Preserving Disease Prediction. | Bin Li, Xiaoqian Jiang, Yu-Chun Hsu, Arif Ozgun Harmanci, Hongchang Gao, Xinghua Shi |
| 2025 | ICDM | Sharpness-Aware Optimization Through Variance Suppression on Deep AUC Maximization. | Xinwen Zhang, Hongchang Gao |
| 2025 | IJCAI | Federated Stochastic Bilevel Optimization with Fully First-Order Gradients. | Yihan Zhang, Rohit Dhaipule, Chiu C. Tan, Haibin Ling, Hongchang Gao |
| 2025 | IWQoS | Joint Swapping and Purification with Failures for Entanglement Distribution in Quantum Networks. | Jiyao Liu, Xinwen Zhang, Xinliang Wei, Xuanzhang Liu, Yuzhou Chen, Hongchang Gao, Yu Wang |
| 2024 | AAAI | Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. | Junjie Chen, Jiahao Li, Chen Song, Bin Li, Qingcai Chen, Hongchang Gao, Wendy Hui Wang, Zenglin Xu, Xinghua Shi |
| 2024 | AISTATS | Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate. | Hongchang Gao |
| 2024 | AISTATS | Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. | Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang |
| 2024 | ICANN | CauchyGCN: Preserving Local Smoothness in Graph Convolutional Networks via a Cauchy-Based Message-Passing Scheme and Clustering Analysis. | Peiyu Liang, Hongchang Gao, Xubin He |
| 2024 | ICML | A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization. | Hongchang Gao |
| 2024 | ICML | A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization. | Xinwen Zhang, Ali Payani, Myungjin Lee, Richard Souvenir, Hongchang Gao |
| 2024 | SDM | Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization. | Hongchang Gao, Yubin Duan, Yihan Zhang, Jie Wu |
| 2023 | AAAI | Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory. | Hongchang Gao |
| 2023 | AISTATS | On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network. | Hongchang Gao, Bin Gu, My T. Thai |
| 2023 | ICCV | Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. | Dong Lu, Zhiqiang Wang, Teng Wang, Weili Guan, Hongchang Gao, Feng Zheng |
| 2023 | ICPP | Group-based Hierarchical Federated Learning: Convergence, Group Formation, and Sampling. | Jiyao Liu, Xinliang Wei, Xuanzhang Liu, Hongchang Gao, Yu Wang |
| 2023 | IJCAI | Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms. | Yihan Zhang, Meikang Qiu, Hongchang Gao |
| 2023 | KDD | Distributed Optimization for Big Data Analytics: Beyond Minimization. | Hongchang Gao, Xinwen Zhang |
| 2022 | AAAI | Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems. | Wenkang Zhan, Gang Wu, Hongchang Gao |
| 2022 | ICML | On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum. | Hongchang Gao, Junyi Li, Heng Huang |
| 2022 | ICML | Gradient-Free Method for Heavily Constrained Nonconvex Optimization. | Wanli Shi, Hongchang Gao, Bin Gu |
| 2022 | WWW | Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction. | Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang |
| 2021 | AAAI | On the Convergence of Communication-Efficient Local SGD for Federated Learning. | Hongchang Gao, An Xu, Heng Huang |
| 2021 | IJCAI | On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. | Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi |
| 2021 | IJCAI | Sample Efficient Decentralized Stochastic Frank-Wolfe Methods for Continuous DR-Submodular Maximization. | Hongchang Gao, Hanzi Xu, Slobodan Vucetic |
| 2021 | KDD | PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. | Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi |
| 2021 | SDM | Faster Stochastic Second Order Method for Large-Scale Machine Learning Models. | Hongchang Gao, Heng Huang |
| 2021 | SDM | Provable Distributed Stochastic Gradient Descent with Delayed Updates. | Hongchang Gao, Gang Wu, Ryan A. Rossi |
| 2020 | ICML | Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems? | Hongchang Gao, Heng Huang |
| 2019 | ICML | Demystifying Dropout. | Hongchang Gao, Jian Pei, Heng Huang |
| 2019 | KDD | Conditional Random Field Enhanced Graph Convolutional Neural Networks. | Hongchang Gao, Jian Pei, Heng Huang |
| 2019 | KDD | ProGAN: Network Embedding via Proximity Generative Adversarial Network. | Hongchang Gao, Jian Pei, Heng Huang |
| 2018 | IJCAI | Joint Generative Moment-Matching Network for Learning Structural Latent Code. | Hongchang Gao, Heng Huang |
| 2018 | IJCAI | Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models. | Hongchang Gao, Heng Huang |
| 2018 | IJCAI | Deep Attributed Network Embedding. | Hongchang Gao, Heng Huang |
| 2018 | KDD | Self-Paced Network Embedding. | Hongchang Gao, Heng Huang |
| 2018 | WWW | Attention Convolutional Neural Network for Advertiser-level Click-through Rate Forecasting. | Hongchang Gao, Deguang Kong, Miao Lu, Xiao Bai, Jian Yang |
| 2017 | AAAI | Local Centroids Structured Non-Negative Matrix Factorization. | Hongchang Gao, Feiping Nie, Heng Huang |
| 2016 | AAAI | The l2, 1-Norm Stacked Robust Autoencoders for Domain Adaptation. | Wenhao Jiang, Hongchang Gao, Fu-Lai Chung, Heng Huang |
| 2016 | ICDM | New Robust Clustering Model for Identifying Cancer Genome Landscapes. | Hongchang Gao, Xiaoqian Wang, Heng Huang |
| 2015 | CIKM | Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF. | Hongchang Gao, Feiping Nie, Tom Weidong Cai, Heng Huang |
| 2015 | ICCV | Multi-view Subspace Clustering. | Hongchang Gao, Feiping Nie, Xuelong Li, Heng Huang |
| 2015 | KDD | Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning. | Hongchang Gao, Lin Yan, Weidong Cai, Heng Huang |
| 2015 | MICCAI | Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. | Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaqun Goi Cortes, Yang Wang, Feiping Nie, John D. West, Andrew J. Saykin, Li Shen, Heng Huang |