Showing 2024Show all
2 papers · 1 filter
math.OC2024
Beyond Convexity: Proximal-Perturbed Lagrangian Methods for Efficient Functional Constrained Optimization
Sang Bin Moon, Jong Gwang Kim, Ashish Chandra +2
Non-convex functional constrained optimization problems have gained substantial attention in machine learning and data science, addressing broad requirements that typically go beyo…
stat.ML2024
Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
Sang Bin Moon, Abolfazl Hashemi
The Adversarial Markov Decision Process (AMDP) is a learning framework that deals with unknown and varying tasks in decision-making applications like robotics and recommendation sy…