4 citations · 15 across the 10 of their papers we have counts for
6 papers · 1 filter
SAU: Sparsity-Aware Unlearning for LLMs via Gradient Masking and Importance Redistribution
Yuze Wang, Yujia Tong, Xuan Liu +1
Large Language Models (LLMs) inevitably memorize sensitive information during training, posing significant privacy risks. Machine unlearning has emerged as a promising solution to…
Advancing Generalized Transfer Attack with Initialization Derived Bilevel Optimization and Dynamic Sequence Truncation
Yaohua Liu, Jiaxin Gao, Xuan Liu +3
Transfer attacks generate significant interest for real-world black-box applications by crafting transferable adversarial examples through surrogate models. Whereas, existing works…
Hierarchical Optimization-Derived Learning
Risheng Liu, Xuan Liu, Shangzhi Zeng +2
In recent years, by utilizing optimization techniques to formulate the propagation of deep model, a variety of so-called Optimization-Derived Learning (ODL) approaches have been pr…
Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training
Risheng Liu, Xuan Liu, Shangzhi Zeng +2
Recently, Optimization-Derived Learning (ODL) has attracted attention from learning and vision areas, which designs learning models from the perspective of optimization. However, p…
Revisiting GANs by Best-Response Constraint: Perspective, Methodology, and Application
Risheng Liu, Jiaxin Gao, Xuan Liu +1
In past years, the minimax type single-level optimization formulation and its variations have been widely utilized to address Generative Adversarial Networks (GANs). Unfortunately,…
Value-Function-based Sequential Minimization for Bi-level Optimization
Risheng Liu, Xuan Liu, Shangzhi Zeng +2
Gradient-based Bi-Level Optimization (BLO) methods have been widely applied to handle modern learning tasks. However, most existing strategies are theoretically designed based on r…