Min-Fong Hong

发表

Distributed Adversarial Training to Robustify Deep Neural Networks at Scale

L. Horesh, Pin-Yu Chen, Quanfu Fan, 2022, ArXiv.

A Framework for Understanding Model Extraction Attack and Defense

Xun Xian, Jie Ding, Min-Fong Hong, 2022, ArXiv.

Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy pdf

Jinfeng Yi, Zhiwei Steven Wu, Xinwei Zhang, 2021, ICML.

A Framework for Understanding Model Extraction Attack and Defense

Xun Xian, Jie Ding, Min-Fong Hong, 2022, ArXiv.

Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization

Shiyu Chang, Prashant Khanduri, Yihua Zhang, 2021, ICML.

Advancing Model Pruning via Bi-level Optimization

Sijia Liu, P. Ram, Pu Zhao, 2022, 2210.04092.

Distributed Adversarial Training to Robustify Deep Neural Networks at Scale

L. Horesh, Pin-Yu Chen, Quanfu Fan, 2022, UAI.

Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence

Shahana Ibrahim, Min-Fong Hong, Wenqiang Pu, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Advancing Model Pruning via Bi-level Optimization

P. Ram, Pu Zhao, Yuguang Yao, 2022, ArXiv.

Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees

Min-Fong Hong, Chenliang Li, Alfredo Garcia, 2022, Neural Information Processing Systems.

Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees

Min-Fong Hong, Chenliang Li, Alfredo Garcia, 2022, NeurIPS.

On the Robustness of deep learning-based MRI Reconstruction to image transformations

Mehmet Akccakaya, Min-Fong Hong, Sijia Liu, 2022, 2211.04930.

Deep Spectrum Cartography: Completing Radio Map Tensors Using Learned Neural Models pdf

Xiao Fu, Mingyi Hong, Sagar Shrestha, 2021, IEEE Transactions on Signal Processing.

What Is Missing in IRM Training and Evaluation? Challenges and Solutions

Kush R. Varshney, K. Varshney, P. Ram, 2023, ICLR.

Advancing Model Pruning via Bi-level Optimization

P. Ram, Pu Zhao, Yuguang Yao, 2022, NeurIPS.

How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective

Jinfeng Yi, Yuguang Yao, Shiyu Chang, 2022, ICLR.

GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data

Xinwei Zhang, Min-Fong Hong, Jie Chen, 2023, ArXiv.

Parallel Assisted Learning

Jie Ding, Xinran Wang, Min-Fong Hong, 2022, IEEE Transactions on Signal Processing.

Understanding Expertise through Demonstrations: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning

Min-Fong Hong, Chenliang Li, Alfredo Garcia, 2023, ArXiv.

Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach

Hoi-To Wai, Jia Liu, Haibo Yang, 2022, ICLR.

Deep Generative Model Learning For Blind Spectrum Cartography with NMF-Based Radio Map Disaggregation

Xiao Fu, Mingyi Hong, Sagar Shrestha, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning pdf

Pramod K. Varshney, Ketan Rajawat, Prashant Khanduri, 2021, NeurIPS.

An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning

Ioannis C. Tsaknakis, Yuguang Yao, Prashant Khanduri, 2023, IEEE Signal Processing Magazine.

Flow-based Intrinsic Curiosity Module

Hsuan-Kung Yang, Min-Fong Hong, Po-Han Chiang, 2019, IJCAI.

Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup

K. Zhang, Tianyi Chen, Min-Fong Hong, 2020, IEEE Transactions on Signal Processing.

Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach

Ioannis C. Tsaknakis, Jia Liu, Jiawei Zhang, 2023, ICML.

Towards Understanding Asynchronous Advantage Actor-Critic: Convergence and Linear Speedup

K. Zhang, Tianyi Chen, Min-Fong Hong, 2020, IEEE Transactions on Signal Processing.

On the Robustness of deep learning-based MRI Reconstruction to image transformations

Mehmet Akccakaya, Min-Fong Hong, Sijia Liu, 2022, 2211.04930.

Vcc: Scaling Transformers to 128K Tokens or More by Prioritizing Important Tokens

Aston Zhang, Cole Hawkins, Nikolaos Pappas, 2023, ArXiv.

Understanding Backdoor Attacks through the Adaptability Hypothesis

G. Wang, Xun Xian, Jie Ding, 2023, ICML.

GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data

Xinwei Zhang, Min-Fong Hong, Jie Chen, 2023, ArXiv.

When Demonstrations meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning

Min-Fong Hong, Alfredo Garcia, Siliang Zeng, 2023, NeurIPS.

Exploration via Flow-Based Intrinsic Rewards

Hsuan-Kung Yang, Chun-Yi Lee, Min-Fong Hong, 2019, ArXiv.