88 citations · 605 across the 80 of their papers we have counts for
7 papers · 1 filter
Efficient Preference Poisoning Attack on Offline RLHF
Chenye Yang, Weiyu Xu, Lifeng Lai
Offline Reinforcement Learning from Human Feedback (RLHF) pipelines such as Direct Preference Optimization (DPO) train on a pre-collected preference dataset, which makes them vulne…
Learn to Change the World: Multi-level Reinforcement Learning with Model-Changing Actions
Ziqing Lu, Babak Hassibi, Lifeng Lai +1
Reinforcement learning usually assumes a given or sometimes even fixed environment in which an agent seeks an optimal policy to maximize its long-term discounted reward. In contras…
Provably Invincible Adversarial Attacks on Reinforcement Learning Systems: A Rate-Distortion Information-Theoretic Approach
Ziqing Lu, Lifeng Lai, Weiyu Xu
Reinforcement learning (RL) for the Markov Decision Process (MDP) has emerged in many security-related applications, such as autonomous driving, financial decisions, and drone/robo…
Feature compression is the root cause of adversarial fragility in neural network classifiers
Jingchao Gao, Ziqing Lu, Raghu Mudumbai +6
In this paper, we uniquely study the adversarial robustness of deep neural networks (NN) for classification tasks against that of optimal classifiers. We look at the smallest magni…
Optimal Cost Constrained Adversarial Attacks For Multiple Agent Systems
Ziqing Lu, Guanlin Liu, Lifeng Lai +1
Finding optimal adversarial attack strategies is an important topic in reinforcement learning and the Markov decision process. Previous studies usually assume one all-knowing coord…
Distributed Dual Coordinate Ascent with Imbalanced Data on a General Tree Network
Myung Cho, Lifeng Lai, Weiyu Xu
In this paper, we investigate the impact of imbalanced data on the convergence of distributed dual coordinate ascent in a tree network for solving an empirical loss minimization pr…