Hongchang Gao - RankMe

69 papers A* 33A 7B 2Journal 23Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Swapping and Purification Scheme Optimization for Entanglement Distribution in Quantum Networks. IEEE Trans. Netw. Jiyao Liu, Xinwen Zhang, Xinliang Wei, Xuanzhang Liu, Yuzhou Chen, Hongchang Gao, Yu Wang
2025	—	`conf`	FSLearning: An Efficient Federated Split Learning Framework for Privacy-Preserving Disease Prediction. AIME (1) Bin Li, Xiaoqian Jiang, Yu-Chun Hsu, Arif Ozgun Harmanci, Hongchang Gao, Xinghua Shi
2025	A*	`conf`	Federated Stochastic Bilevel Optimization with Fully First-Order Gradients. IJCAI Yihan Zhang, Rohit Dhaipule, Chiu C. Tan, Haibin Ling, Hongchang Gao
2025	J	`jnl`	Federated Stochastic Minimax Optimization under Heavy-Tailed Noises. CoRR Xinwen Zhang, Hongchang Gao
2025	B	`conf`	Joint Swapping and Purification with Failures for Entanglement Distribution in Quantum Networks. IWQoS Jiyao Liu, Xinwen Zhang, Xinliang Wei, Xuanzhang Liu, Yuzhou Chen, Hongchang Gao, Yu Wang
2025	J	`jnl`	Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noises. CoRR Xinwen Zhang, Yihan Zhang, Hongchang Gao
2025	J	`jnl`	On Provable Benefits of Muon in Federated Learning. CoRR Xinwen Zhang, Hongchang Gao
2025	A*	`conf`	Sharpness-Aware Optimization Through Variance Suppression on Deep AUC Maximization. ICDM Xinwen Zhang, Hongchang Gao
2024	A*	`conf`	A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization. ICML Hongchang Gao
2024	A*	`conf`	A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization. ICML Xinwen Zhang, Ali Payani, Myungjin Lee, Richard Souvenir, Hongchang Gao
2024	J	`jnl`	AMOSL: Adaptive Modality-wise Structure Learning in Multi-view Graph Neural Networks For Enhanced Unified Representation. CoRR Peiyu Liang, Hongchang Gao, Xubin He
2024	A	`conf`	Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning. AISTATS Taeuk Jang, Hongchang Gao, Pengyi Shi, Xiaoqian Wang
2024	—	`conf`	CauchyGCN: Preserving Local Smoothness in Graph Convolutional Networks via a Cauchy-Based Message-Passing Scheme and Clustering Analysis. ICANN (5) Peiyu Liang, Hongchang Gao, Xubin He
2024	A	`conf`	Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate. AISTATS Hongchang Gao
2024	A	`conf`	Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization. SDM Hongchang Gao, Yubin Duan, Yihan Zhang, Jie Wu
2024	A*	`conf`	Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks. AAAI Junjie Chen, Jiahao Li, Chen Song, Bin Li, Qingcai Chen, Hongchang Gao, Wendy Hui Wang, Zenglin Xu, Xinghua Shi
2024	J	`jnl`	Gradient-Free Method for Heavily Constrained Nonconvex Optimization. CoRR Wanli Shi, Hongchang Gao, Bin Gu
2024	J	`jnl`	Group Formation and Sampling in Group-Based Hierarchical Federated Learning. IEEE Trans. Cloud Comput. Jiyao Liu, Xuanzhang Liu, Xinliang Wei, Hongchang Gao, Yu Wang
2024	J	`jnl`	Measuring privacy policy compliance in the Alexa ecosystem: In-depth analysis. Comput. Secur. Hassan A. Shafei, Hongchang Gao, Chiu C. Tan
2023	J	`jnl`	Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization. CoRR Hongchang Gao
2023	J	`jnl`	Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems? CoRR Yihan Zhang, Wenhao Jiang, Feng Zheng, Chiu C. Tan, Xinghua Shi, Hongchang Gao
2023	A*	`conf`	Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms. IJCAI Yihan Zhang, Meikang Qiu, Hongchang Gao
2023	A*	`conf`	Distributed Optimization for Big Data Analytics: Beyond Minimization. KDD Hongchang Gao, Xinwen Zhang
2023	A*	`conf`	Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory. AAAI Hongchang Gao
2023	—	`conf`	FedDP: Secure Federated Learning with Differential Privacy for Disease Prediction. ICCABS Bin Li, Hongchang Gao, Xinghua Shi
2023	A*	`conf`	Federated Compositional Deep AUC Maximization. NeurIPS Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao
2023	J	`jnl`	Federated Compositional Deep AUC Maximization. CoRR Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao
2023	B	`conf`	Group-based Hierarchical Federated Learning: Convergence, Group Formation, and Sampling. ICPP Jiyao Liu, Xinliang Wei, Xuanzhang Liu, Hongchang Gao, Yu Wang
2023	J	`jnl`	On the Communication Complexity of Decentralized Bilevel Optimization. CoRR Yihan Zhang, My T. Thai, Jie Wu, Hongchang Gao
2023	A	`conf`	On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network. AISTATS Hongchang Gao, Bin Gu, My T. Thai
2023	A*	`conf`	Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. ICCV Dong Lu, Zhiqiang Wang, Teng Wang, Weili Guan, Hongchang Gao, Feng Zheng
2023	J	`jnl`	Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models. CoRR Dong Lu, Zhiqiang Wang, Teng Wang, Weili Guan, Hongchang Gao, Feng Zheng
2023	J	`jnl`	Stochastic Multi-Level Compositional Optimization Algorithms over Networks with Level-Independent Convergence Rate. CoRR Hongchang Gao
2023	J	`jnl`	When Decentralized Optimization Meets Federated Learning. CoRR Hongchang Gao, My T. Thai, Jie Wu
2023	J	`jnl`	When Decentralized Optimization Meets Federated Learning. IEEE Netw. Hongchang Gao, My T. Thai, Jie Wu
2022	J	`jnl`	Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems. CoRR Hongchang Gao
2022	A*	`conf`	Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems. AAAI Wenkang Zhan, Gang Wu, Hongchang Gao
2022	A*	`conf`	Gradient-Free Method for Heavily Constrained Nonconvex Optimization. ICML Wanli Shi, Hongchang Gao, Bin Gu
2022	A*	`conf`	On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum. ICML Hongchang Gao, Junyi Li, Heng Huang
2022	J	`jnl`	On the Convergence of Momentum-Based Algorithms for Federated Stochastic Bilevel Optimization Problems. CoRR Hongchang Gao
2022	A*	`conf`	Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction. WWW Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang
2022	J	`jnl`	Stochastic Bilevel Distributed Optimization over a Network. CoRR Hongchang Gao, Bin Gu, My T. Thai
2021	A*	`conf`	Fast Training Method for Stochastic Compositional Optimization Problems. NeurIPS Hongchang Gao, Heng Huang
2021	A	`conf`	Faster Stochastic Second Order Method for Large-Scale Machine Learning Models. SDM Hongchang Gao, Heng Huang
2021	A*	`conf`	On the Convergence of Communication-Efficient Local SGD for Federated Learning. AAAI Hongchang Gao, An Xu, Heng Huang
2021	A*	`conf`	On the Convergence of Stochastic Compositional Gradient Descent Ascent Method. IJCAI Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi
2021	A*	`conf`	PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks. KDD Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi
2021	A	`conf`	Provable Distributed Stochastic Gradient Descent with Delayed Updates. SDM Hongchang Gao, Gang Wu, Ryan A. Rossi
2021	A*	`conf`	Sample Efficient Decentralized Stochastic Frank-Wolfe Methods for Continuous DR-Submodular Maximization. IJCAI Hongchang Gao, Hanzi Xu, Slobodan Vucetic
2020	J	`jnl`	Adaptive Serverless Learning. CoRR Hongchang Gao, Heng Huang
2020	A*	`conf`	Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems? ICML Hongchang Gao, Heng Huang
2020	J	`jnl`	Periodic Stochastic Gradient Descent with Momentum for Decentralized Training. CoRR Hongchang Gao, Heng Huang
2020	J	`jnl`	Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model. IEEE Trans. Neural Networks Learn. Syst. Kamran Ghasedi Dizaji, Hongchang Gao, Yanhua Yang, Heng Huang, Cheng Deng
2019	A*	`conf`	Conditional Random Field Enhanced Graph Convolutional Neural Networks. KDD Hongchang Gao, Jian Pei, Heng Huang
2019	A*	`conf`	Demystifying Dropout. ICML Hongchang Gao, Jian Pei, Heng Huang
2019	A*	`conf`	ProGAN: Network Embedding via Proximity Generative Adversarial Network. KDD Hongchang Gao, Jian Pei, Heng Huang
2019	J	`jnl`	Stacked Robust Adaptively Regularized Auto-Regressions for Domain Adaptation. IEEE Trans. Knowl. Data Eng. Wenhao Jiang, Hongchang Gao, Wei Lu, Wei Liu, Fu-Lai Chung, Heng Huang
2018	A*	`conf`	Attention Convolutional Neural Network for Advertiser-level Click-through Rate Forecasting. WWW Hongchang Gao, Deguang Kong, Miao Lu, Xiao Bai, Jian Yang
2018	A*	`conf`	Deep Attributed Network Embedding. IJCAI Hongchang Gao, Heng Huang
2018	A*	`conf`	Joint Generative Moment-Matching Network for Learning Structural Latent Code. IJCAI Hongchang Gao, Heng Huang
2018	A*	`conf`	Self-Paced Network Embedding. KDD Hongchang Gao, Heng Huang
2018	A*	`conf`	Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models. IJCAI Hongchang Gao, Heng Huang
2017	A*	`conf`	Local Centroids Structured Non-Negative Matrix Factorization. AAAI Hongchang Gao, Feiping Nie, Heng Huang
2016	A*	`conf`	New Robust Clustering Model for Identifying Cancer Genome Landscapes. ICDM Hongchang Gao, Xiaoqian Wang, Heng Huang
2016	A*	`conf`	The l2, 1-Norm Stacked Robust Autoencoders for Domain Adaptation. AAAI Wenhao Jiang, Hongchang Gao, Fu-Lai Chung, Heng Huang
2015	A*	`conf`	Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning. KDD Hongchang Gao, Lin Yan, Weidong Cai, Heng Huang
2015	—	`conf`	Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut. MICCAI (2) Hongchang Gao, Chengtao Cai, Jingwen Yan, Lin Yan, Joaquín Goñi Cortes, Yang Wang, Feiping Nie, John D. West, Andrew J. Saykin, Li Shen, Heng Huang
2015	A*	`conf`	Multi-view Subspace Clustering. ICCV Hongchang Gao, Feiping Nie, Xuelong Li, Heng Huang
2015	A	`conf`	Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF. CIKM Hongchang Gao, Feiping Nie, Tom Weidong Cai, Heng Huang