3 papers
cs.LG2025
Controllable Machine Unlearning via Gradient Pivoting
Youngsik Hwang, Dong-Young Lim
Machine unlearning (MU) aims to remove the influence of specific data from a trained model. However, approximate unlearning methods, often formulated as a single-objective optimiza…
stat.ML2025
DGSAM: Domain Generalization via Individual Sharpness-Aware Minimization
Youngjun Song, Youngsik Hwang, Jonghun Lee +2
Domain generalization (DG) aims to learn models that perform well on unseen target domains by training on multiple source domains. Sharpness-Aware Minimization (SAM), known for fin…
cs.LG2024
Dual Cone Gradient Descent for Training Physics-Informed Neural Networks
Youngsik Hwang, Dong-Young Lim
Physics-informed neural networks (PINNs) have emerged as a prominent approach for solving partial differential equations (PDEs) by minimizing a combined loss function that incorpor…