1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2025
A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning
Zhehao Huang, Xinwen Cheng, Jie Zhang +5
Recent advancements in deep models have highlighted the need for intelligent systems that combine continual learning (CL) for knowledge acquisition with machine unlearning (MU) for…
cs.CV2025
Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
Dang Nguyen, Jiping Li, Jinghao Zheng +1
Synthetically augmenting training datasets with diffusion models has become an effective strategy for improving the generalization of image classifiers. However, existing approache…
cs.LG2024★ 1 cited
Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement
Zhehao Huang, Xinwen Cheng, JingHao Zheng +4
Machine unlearning (MU) has emerged to enhance the privacy and trustworthiness of deep neural networks. Approximate MU is a practical method for large-scale models. Our investigati…