9 citations · 17 across the 8 of their papers we have counts for
10 papers
Longitudinal Bayesian Learning of Continuous Disease Position across the Alzheimer's Disease Continuum
Yingying Zhang, Kun Zhao, Guodong Liu +10
Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remain limited to discrete diagnosi…
Gradient-Free Method for Heavily Constrained Nonconvex Optimization
Wanli Shi, Hongchang Gao, Bin Gu
Zeroth-order (ZO) method has been shown to be a powerful method for solving the optimization problem where explicit expression of the gradients is difficult or infeasible to obtain…
On the Communication Complexity of Decentralized Stochastic Bilevel Optimization
Yihan Zhang, My T. Thai, Jie Wu +1
Stochastic bilevel optimization finds widespread applications in machine learning, including meta-learning, hyperparameter optimization, and neural architecture search. To extend s…
Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization
Hongchang Gao
The stochastic compositional minimax problem has attracted a surge of attention in recent years since it covers many emerging machine learning models. Meanwhile, due to the emergen…
Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models
Dong Lu, Zhiqiang Wang, Teng Wang +3
Vision-language pre-training (VLP) models have shown vulnerability to adversarial examples in multimodal tasks. Furthermore, malicious adversaries can be deliberately transferred t…
When Decentralized Optimization Meets Federated Learning
Hongchang Gao, My T. Thai, Jie Wu
Federated learning is a new learning paradigm for extracting knowledge from distributed data. Due to its favorable properties in preserving privacy and saving communication costs,…