4 papers
DP-Muon: Differentially Private Optimization via Matrix-Orthogonalized Momentum
Jihwan Kim, Chenglin Fan
We study differentially private (DP) training with Muon, a matrix-valued optimizer that updates hidden-layer weights using momentum followed by Newton--Schulz orthogonalization. Wh…
Robust and Consistent Ski Rental with Distributional Advice
Jihwan Kim, Chenglin Fan
The ski rental problem is a canonical model for online decision-making under uncertainty, capturing the fundamental trade-off between repeated rental costs and a one-time purchase.…
Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering
Chenglin Fan, Dahoon Lee, Euiwoong Lee
Correlation Clustering (CC) is a foundational problem in unsupervised learning that models binary similarity relations using labeled graphs. While classical CC has been widely stud…
1.64-Approximation for Chromatic Correlation Clustering via Chromatic Cluster LP
Dahoon Lee, Chenglin Fan, Euiwoong Lee
Chromatic Correlation Clustering (CCC) generalizes Correlation Clustering by assigning multiple categorical relationships (colors) to edges and imposing chromatic constraints on th…