331 citations · 468 across the 14 of their papers we have counts for
4 papers · 1 filter
Learning context-aware adaptive solvers to accelerate quadratic programming
Haewon Jung, Junyoung Park, Jinkyoo Park
Convex quadratic programming (QP) is an important sub-field of mathematical optimization. The alternating direction method of multipliers (ADMM) is a successful method to solve QP.…
Neuro CROSS exchange: Learning to CROSS exchange to solve realistic vehicle routing problems
Minjun Kim, Junyoung Park, Jinkyoo Park
CROSS exchange (CE), a meta-heuristic that solves various vehicle routing problems (VRPs), improves the solutions of VRPs by swapping the sub-tours of the vehicles. Inspired by CE,…
Meta-SysId: A Meta-Learning Approach for Simultaneous Identification and Prediction
Junyoung Park, Federico Berto, Arec Jamgochian +2
In this paper, we propose Meta-SysId, a meta-learning approach to model sets of systems that have behavior governed by common but unknown laws and that differentiate themselves by…
Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization
Minsu Kim, Junyoung Park, Jinkyoo Park
Deep reinforcement learning (DRL)-based combinatorial optimization (CO) methods (i.e., DRL-NCO) have shown significant merit over the conventional CO solvers as DRL-NCO is capable…