4 citations · 5 across the 13 of their papers we have counts for
5 papers · 1 filter
Post-Training and Test-Time Scaling of Generative Agent Behavior Models for Interactive Autonomous Driving
Hyunki Seong, Jeong-Kyun Lee, Heesoo Myeong +5
Learning interactive motion behaviors among multiple agents is a core challenge in autonomous driving. While imitation learning models generate realistic trajectories, they often i…
Approximating (Weighted) Chromatic Correlation Clustering via Cluster LP
Fateme Abbasi, Hyung-Chan An, Jarosław Byrka +2
Correlation Clustering is a fundamental clustering problem that is generalized to Chromatic Correlation Clustering to incorporate categorical data. Both problems have been intensiv…
Online Rounding Schemes for Edge Cover
Jarosław Byrka, Yongho Shin
Linear programming rounding is a fundamental technique in the design of approximation and online algorithms. A growing body of work has investigated online rounding schemes for var…
Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach
Changyeol Lee, Yongho Shin, Hyung-Chan An
Clustering is a fundamental task in both machine learning and data mining. Among various methods, edge-colored clustering (ECC) has emerged as a useful approach for handling catego…
Learning-Augmented Online Bipartite Fractional Matching
Davin Choo, Billy Jin, Yongho Shin
Online bipartite matching is a fundamental problem in online optimization, extensively studied both in its integral and fractional forms due to its theoretical significance and pra…