3 papers
cs.LG2026
Why Some Models Resist Unlearning: A Linear Stability Perspective
Wei-Kai Chang, Rajiv Khanna
Machine unlearning, the ability to erase the effect of specific training samples without retraining from scratch, is critical for privacy, regulation, and efficiency. However, most…
cs.LG2025
Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes
Wei-Kai Chang, Rajiv Khanna
As deep learning models continue to scale, the growing computational demands have amplified the need for effective coreset selection techniques. Coreset selection aims to accelerat…
cs.LG2025
A Unified Stability Analysis of SAM vs SGD: Role of Data Coherence and Emergence of Simplicity Bias
Wei-Kai Chang, Rajiv Khanna
Understanding the dynamics of optimization in deep learning is increasingly important as models scale. While stochastic gradient descent (SGD) and its variants reliably find soluti…