Hongchang Gao

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All published works

Action	Title	Year	Authors
+ PDF Chat	Gradient-Free Method for Heavily Constrained Nonconvex Optimization	2024	Wanli Shi Hongchang Gao Bin Gu
+ PDF Chat	AMOSL: Adaptive Modality-wise Structure Learning in Multi-view Graph Neural Networks For Enhanced Unified Representation	2024	Peiyu Liang Hongchang Gao Xubin He
+ PDF Chat	AMOSL: Adaptive Modality-Wise Structure Learning in Multi-View Graph Neural Networks for Enhanced Unified Representation	2024	Peiyu Liang Hongchang Gao Xubin He
+	Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization	2024	Hongchang Gao Yubin Duan Yihan Zhang Jie Wu
+ PDF Chat	Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models	2023	Lu Dong Zhiqiang Wang Teng Wang Weili Guan Hongchang Gao Feng Zheng
+ PDF Chat	When Decentralized Optimization Meets Federated Learning	2023	Hongchang Gao My T. Thai Jie Wu
+	Federated Compositional Deep AUC Maximization	2023	Xinwen Zhang Yihan Zhang Tianbao Yang Richard Souvenir Hongchang Gao
+	Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems?	2023	Yihan Zhang Wenhao Jiang Feng Zheng Chiu C. Tan Xinghua Shi Hongchang Gao
+	When Decentralized Optimization Meets Federated Learning	2023	Hongchang Gao My T. Thai Jie Wu
+	Stochastic Multi-Level Compositional Optimization Algorithms over Networks with Level-Independent Convergence Rate	2023	Hongchang Gao
+	Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization	2023	Hongchang Gao
+	Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models	2023	Lu Dong Zhiqiang Wang Teng Wang Weili Guan Hongchang Gao Feng Zheng
+	On the Communication Complexity of Decentralized Bilevel Optimization	2023	Yihan Zhang My T. Thai Jie Wu Hongchang Gao
+	On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network	2022	Hongchang Gao Bin Gu My T. Thai
+	Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems	2022	Hongchang Gao
+	Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?	2020	Hongchang Gao Heng Huang
+	Periodic Stochastic Gradient Descent with Momentum for Decentralized Training	2020	Hongchang Gao Heng Huang
+	Adaptive Serverless Learning	2020	Hongchang Gao Heng Huang

Common Coauthors

Coauthor	Papers Together
Yihan Zhang	4
My T. Thai	4
Jie Wu	3
Heng Huang	3
Zhiqiang Wang	2
Weili Guan	2
Peiyu Liang	2
Lu Dong	2
Xubin He	2
Teng Wang	1
Jie Wu	1
Xinwen Zhang	1
Feng Zheng	1
Chiu C. Tan	1
Xinghua Shi	1
Bin Gu	1
Feng Zheng	1
Yubin Duan	1
Tianbao Yang	1
Wenhao Jiang	1
Richard Souvenir	1
Feng Zheng	1
Bin Gu	1
Wanli Shi	1
Teng Wang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	3
+	Communication Compression for Decentralized Training	2018	Hanlin Tang Shaoduo Gan Ce Zhang Tong Zhang Liu Ji	2
+	signSGD: Compressed Optimisation for Non-Convex Problems	2018	Jeremy Bernstein Yu-Xiang Wang Kamyar Azizzadenesheli Animashree Anandkumar	2
+	Robust and Communication-Efficient Collaborative Learning	2019	Amirhossein Reisizadeh Hossein Taheri Aryan Mokhtari Hamed Hassani Ramtin Pedarsani	2
+	A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization	2019	Sulaiman A. Alghunaim Kun Yuan Ali H. Sayed	2
+	Sparsified SGD with Memory	2018	Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi	2
+	QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding	2016	Dan Alistarh Demjan Grubic Jerry Li Ryota Tomioka Milan Vojnović	2
+	TernGrad: ternary gradients to reduce communication in distributed deep learning	2017	Wei Wen Cong Xu Feng Yan Chunpeng Wu Yandan Wang Yiran Chen Hai Li	2
+ PDF Chat	Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations	2015	John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono	1
+	On the Global Linear Convergence of Frank-Wolfe Optimization Variants	2015	Simon Lacoste-Julien Martin Jaggi	1
+	Conditional Gradient Sliding for Convex Optimization	2016	Guanghui Lan Yi Zhou	1
+	Convergence Rate of Frank-Wolfe for Non-Convex Objectives	2016	Simon Lacoste-Julien	1
+	Wide & Deep Learning for Recommender Systems	2016	Heng-Tze Cheng Levent Koç Jeremiah Harmsen Tal Shaked Tushar Chandra Hrishi Aradhye Glen Anderson Greg S. Corrado Wei Koong Chai Mustafa Ispir	1
+ PDF Chat	Deep Visual-Semantic Alignments for Generating Image Descriptions	2016	Andrej Karpathy Li Fei-Fei	1
+ PDF Chat	Modeling Context in Referring Expressions	2016	Licheng Yu Patrick Poirson Shan Yang Alexander C. Berg Tamara L. Berg	1
+ PDF Chat	SPICE: Semantic Propositional Image Caption Evaluation	2016	Peter Anderson Basura Fernando Mark Johnson Stephen Jay Gould	1
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	1
+ PDF Chat	Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models	2016	Bryan A. Plummer Liwei Wang Chris M. Cervantes Juan C. Caicedo Julia Hockenmaier Svetlana Lazebnik	1
+	Optimal algorithms for smooth and strongly convex distributed optimization in networks	2017	Kevin G. Seaman Francis Bach Sébastien Bubeck Yin Tat Lee Laurent Massoulié	1
+ PDF Chat	Distance Metric Learning Using Graph Convolutional Networks: Application to Functional Brain Networks	2017	Sofia Ira Ktena Sarah Parisot Enzo Ferrante Martin Rajchl Matthew Lee Ben Glocker Daniel Rueckert	1
+	Neural Message Passing for Quantum Chemistry	2017	Justin Gilmer Samuel S. Schoenholz Patrick Riley Oriol Vinyals George E. Dahl	1
+ PDF Chat	Boosting Adversarial Attacks with Momentum	2018	Yinpeng Dong Fangzhou Liao Tianyu Pang Hang Su Jun Zhu Xiaolin Hu Jianguo Li	1
+	On the Convergence of Adam and Beyond	2019	Sashank J. Reddi Satyen Kale Sanjiv Kumar	1
+	On the Differentiability of the Solution to Convex Optimization Problems	2018	Shane Barratt	1
+	Local SGD Converges Fast and Communicates Little	2018	Sebastian U. Stich	1
+	Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules	2018	B. A. Knyazev Xiao Mei Lin Mohamed R. Amer Graham W. Taylor	1
+	Applied Federated Learning: Improving Google Keyboard Query Suggestions	2018	Timothy T. Yang Galen Andrew Hubert Eichner Haicheng Sun Wei Li Nicholas Kong Daniel Ramage Françoise Beaufays	1
+	Gromov-Wasserstein Learning for Graph Matching and Node Embedding	2019	Hongteng Xu Dixin Luo Hongyuan Zha Lawrence Carin	1
+	Complexities in Projection-Free Stochastic Non-convex Minimization	2019	Zebang Shen Cong Fang Peilin Zhao Junzhou Huang Hui Qian	1
+	On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization	2019	Hao Yu Rong Jin Sen Yang	1
+	DeepFM: A Factorization-Machine based Neural Network for CTR Prediction	2017	Huifeng Guo Ruiming Tang Yunming Ye Zhenguo Li Xiuqiang He	1
+ PDF Chat	Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty	2019	Muhammad Raza Khan Joshua Blumenstock	1
+	Hierarchical Graph Representation Learning with Differentiable Pooling	2018	Rex Ying Jiaxuan You Christopher Morris Xiang Ren William L. Hamilton Jure Leskovec	1
+	Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates	2018	Krishnakumar Balasubramanian Saeed Ghadimi	1
+	Stochastic Gradient Push for Distributed Deep Learning	2018	Mahmoud Assran Nicolas Loizou Nicolas Ballas Michael Rabbat	1
+	SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient	2017	Lam M. Nguyen Jie Liu Katya Scheinberg Martin Takáč	1
+	How Powerful are Graph Neural Networks?	2018	Keyulu Xu Weihua Hu Jure Leskovec Stefanie Jegelka	1
+	Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers	2018	Ji Gao Jack Lanchantin Mary Lou Soffa Yanjun Qi	1
+ PDF Chat	Improving Transferability of Adversarial Examples With Input Diversity	2019	Cihang Xie Zhishuai Zhang Yuyin Zhou Song Bai Jianyu Wang Zhou Ren Alan Yuille	1
+ PDF Chat	CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters	2018	Ron Levie Federico Monti Xavier Bresson Michael M. Bronstein	1
+	Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization	2018	Sijia Liu Bhavya Kailkhura Pin‐Yu Chen Paishun Ting Shiyu Chang Lisa Amini	1
+	Decentralized Deep Learning with Arbitrary Communication Compression	2019	Anastasia Koloskova Tao Lin Sebastian U. Stich Martin Jaggi	1
+	SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path-Integrated Differential Estimator	2018	Cong Fang Chris Junchi Li Zhouchen Lin Tong Zhang	1
+	Non-convex Finite-Sum Optimization Via SCSG Methods	2017	Lihua Lei Cheng Ju Jianbo Chen Michael I. Jordan	1
+	Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training	2018	Yujun Lin Song Han Huizi Mao Yu Wang William J. Dally	1
+ PDF Chat	Towards Evaluating the Robustness of Neural Networks	2017	Nicholas Carlini David Wagner	1
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	1
+	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	2016	Michaël Defferrard Xavier Bresson Pierre Vandergheynst	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+	Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks	2019	Jiadong Lin Chuanbiao Song Kun He Liwei Wang John E. Hopcroft	1