Hongchang Gao

Orcid: 0000-0002-0121-0953

According to our database1, Hongchang Gao authored at least 55 papers between 2015 and 2024.

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Bibliography

2024
AMOSL: Adaptive Modality-wise Structure Learning in Multi-view Graph Neural Networks For Enhanced Unified Representation.
CoRR, 2024

Measuring privacy policy compliance in the Alexa ecosystem: In-depth analysis.
Comput. Secur., 2024

Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

CauchyGCN: Preserving Local Smoothness in Graph Convolutional Networks via a Cauchy-Based Message-Passing Scheme and Clustering Analysis.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024

Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Discriminative Forests Improve Generative Diversity for Generative Adversarial Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
When Decentralized Optimization Meets Federated Learning.
IEEE Netw., September, 2023

On the Communication Complexity of Decentralized Bilevel Optimization.
CoRR, 2023

Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization.
CoRR, 2023

Stochastic Multi-Level Compositional Optimization Algorithms over Networks with Level-Independent Convergence Rate.
CoRR, 2023

Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems?
CoRR, 2023

Federated Compositional Deep AUC Maximization.
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.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Communication-Efficient Stochastic Gradient Descent Ascent with Momentum Algorithms.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Group-based Hierarchical Federated Learning: Convergence, Group Formation, and Sampling.
Proceedings of the 52nd International Conference on Parallel Processing, 2023

Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems.
CoRR, 2022

Stochastic Bilevel Distributed Optimization over a Network.
CoRR, 2022

On the Convergence of Momentum-Based Algorithms for Federated Stochastic Bilevel Optimization Problems.
CoRR, 2022

Robust Self-Supervised Structural Graph Neural Network for Social Network Prediction.
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.
Proceedings of the International Conference on Machine Learning, 2022

On the Convergence of Local Stochastic Compositional Gradient Descent with Momentum.
Proceedings of the International Conference on Machine Learning, 2022

Efficient Decentralized Stochastic Gradient Descent Method for Nonconvex Finite-Sum Optimization Problems.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Provable Distributed Stochastic Gradient Descent with Delayed Updates.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Faster Stochastic Second Order Method for Large-Scale Machine Learning Models.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Fast Training Method for Stochastic Compositional Optimization Problems.
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.
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.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On the Convergence of Stochastic Compositional Gradient Descent Ascent Method.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

On the Convergence of Communication-Efficient Local SGD for Federated Learning.
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.
IEEE Trans. Neural Networks Learn. Syst., 2020

Periodic Stochastic Gradient Descent with Momentum for Decentralized Training.
CoRR, 2020

Adaptive Serverless Learning.
CoRR, 2020

Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Stacked Robust Adaptively Regularized Auto-Regressions for Domain Adaptation.
IEEE Trans. Knowl. Data Eng., 2019

ProGAN: Network Embedding via Proximity Generative Adversarial Network.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Conditional Random Field Enhanced Graph Convolutional Neural Networks.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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

2018
Attention Convolutional Neural Network for Advertiser-level Click-through Rate Forecasting.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Self-Paced Network Embedding.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Attributed Network Embedding.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Joint Generative Moment-Matching Network for Learning Structural Latent Code.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
Local Centroids Structured Non-Negative Matrix Factorization.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
New Robust Clustering Model for Identifying Cancer Genome Landscapes.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

The l2, 1-Norm Stacked Robust Autoencoders for Domain Adaptation.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Identifying Connectome Module Patterns via New Balanced Multi-graph Normalized Cut.
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.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Multi-view Subspace Clustering.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Robust Capped Norm Nonnegative Matrix Factorization: Capped Norm NMF.
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015


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