Hongchang Gao

According to our database, Hongchang Gao authored at least 48 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

When Decentralized Optimization Meets Federated Learning.

Hongchang Gao, My T. Thai, Jie Wu

IEEE Netw., September, 2023

On the Communication Complexity of Decentralized Bilevel Optimization.

Yihan Zhang, My T. Thai, Jie Wu, Hongchang Gao

CoRR, 2023

Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization.

Hongchang Gao

CoRR, 2023

Stochastic Multi-Level Compositional Optimization Algorithms over Networks with Level-Independent Convergence Rate.

Hongchang Gao

CoRR, 2023

When Decentralized Optimization Meets Federated Learning.

Hongchang Gao, My T. Thai, Jie Wu

CoRR, 2023

Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems?

Yihan Zhang, Wenhao Jiang, Feng Zheng, Chiu C. Tan, Xinghua Shi, Hongchang Gao

CoRR, 2023

Federated Compositional Deep AUC Maximization.

Xinwen Zhang, Yihan Zhang, Tianbao Yang, Richard Souvenir, Hongchang Gao

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distributed Optimization for Big Data Analytics: Beyond Minimization.

Hongchang Gao, Xinwen Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms.

Yihan Zhang, Meikang Qiu, Hongchang Gao

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Group-based Hierarchical Federated Learning: Convergence, Group Formation, and Sampling.

Jiyao Liu, Xinliang Wei, Xuanzhang Liu, Hongchang Gao, Yu Wang

Proceedings of the 52nd International Conference on Parallel Processing, 2023

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network.

Hongchang Gao, Bin Gu, My T. Thai

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory.

Hongchang Gao

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems.

Hongchang Gao

CoRR, 2022

Stochastic Bilevel Distributed Optimization over a Network.

Hongchang Gao, Bin Gu, My T. Thai

CoRR, 2022

On the Convergence of Momentum-Based Algorithms for Federated Stochastic Bilevel Optimization Problems.

Hongchang Gao

CoRR, 2022

Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction.

Yanfu Zhang, Hongchang Gao, Jian Pei, Heng Huang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Gradient-Free Method for Heavily Constrained Nonconvex Optimization.

Wanli Shi, Hongchang Gao, Bin Gu

Proceedings of the International Conference on Machine Learning, 2022

On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum.

Hongchang Gao, Junyi Li, Heng Huang

Proceedings of the International Conference on Machine Learning, 2022

Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems.

Wenkang Zhan, Gang Wu, Hongchang Gao

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Provable Distributed Stochastic Gradient Descent with Delayed Updates.

Hongchang Gao, Gang Wu, Ryan A. Rossi

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Faster Stochastic Second Order Method for Large-Scale Machine Learning Models.

Hongchang Gao, Heng Huang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Fast Training Method for Stochastic Compositional Optimization Problems.

Hongchang Gao, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks.

Junjie Chen, Wendy Hui Wang, Hongchang Gao, Xinghua Shi

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Sample Efficient Decentralized Stochastic Frank-Wolfe Methods for Continuous DR-Submodular Maximization.

Hongchang Gao, Hanzi Xu, Slobodan Vucetic

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On the Convergence of Stochastic Compositional Gradient Descent Ascent Method.

Hongchang Gao, Xiaoqian Wang, Lei Luo, Xinghua Shi

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On the Convergence of Communication-Efficient Local SGD for Federated Learning.

Hongchang Gao, An Xu, Heng Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model.

Kamran Ghasedi Dizaji, Hongchang Gao, Yanhua Yang, Heng Huang, Cheng Deng

IEEE Trans. Neural Networks Learn. Syst., 2020

Periodic Stochastic Gradient Descent with Momentum for Decentralized Training.

Hongchang Gao, Heng Huang

CoRR, 2020

Adaptive Serverless Learning.

Hongchang Gao, Heng Huang

CoRR, 2020

Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?

Hongchang Gao, Heng Huang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Stacked Robust Adaptively Regularized Auto-Regressions for Domain Adaptation.

Wenhao Jiang, Hongchang Gao, Wei Lu, Wei Liu, Fu-Lai Chung, Heng Huang

IEEE Trans. Knowl. Data Eng., 2019

ProGAN: Network Embedding via Proximity Generative Adversarial Network.

Hongchang Gao, Jian Pei, Heng Huang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Conditional Random Field Enhanced Graph Convolutional Neural Networks.

Hongchang Gao, Jian Pei, Heng Huang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Demystifying Dropout.

Hongchang Gao, Jian Pei, Heng Huang

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Attention Convolutional Neural Network for Advertiser-level Click-through Rate Forecasting.

Hongchang Gao, Deguang Kong, Miao Lu, Xiao Bai, Jian Yang

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Self-Paced Network Embedding.

Hongchang Gao, Heng Huang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Attributed Network Embedding.

Hongchang Gao, Heng Huang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models.

Hongchang Gao, Heng Huang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Joint Generative Moment-Matching Network for Learning Structural Latent Code.

Hongchang Gao, Heng Huang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Local Centroids Structured Non-Negative Matrix Factorization.

Hongchang Gao, Feiping Nie, Heng Huang

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

New Robust Clustering Model for Identifying Cancer Genome Landscapes.

Hongchang Gao, Xiaoqian Wang, Heng Huang

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

The l2, 1-Norm Stacked Robust Autoencoders for Domain Adaptation.

Wenhao Jiang, Hongchang Gao, Fu-Lai Chung, Heng Huang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut.

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

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

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

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Multi-view Subspace Clustering.

Hongchang Gao, Feiping Nie, Xuelong Li, Heng Huang

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF.

Hongchang Gao, Feiping Nie, Tom Weidong Cai, Heng Huang

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015