122 citations · 279 across the 10 of their papers we have counts for
4 papers · 1 filter
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration
Jasmin Brandt, Elias Schede, Viktor Bengs +3
We study the algorithm configuration (AC) problem, in which one seeks to find an optimal parameter configuration of a given target algorithm in an automated way. Recently, there ha…
Simulation-guided Beam Search for Neural Combinatorial Optimization
Jinho Choo, Yeong-Dae Kwon, Jihoon Kim +4
Neural approaches for combinatorial optimization (CO) equip a learning mechanism to discover powerful heuristics for solving complex real-world problems. While neural approaches ca…
Efficient Active Search for Combinatorial Optimization Problems
André Hottung, Yeong-Dae Kwon, Kevin Tierney
Recently numerous machine learning based methods for combinatorial optimization problems have been proposed that learn to construct solutions in a sequential decision process via r…
Learning How to Optimize Black-Box Functions With Extreme Limits on the Number of Function Evaluations
Carlos Ansotegui, Meinolf Sellmann, Tapan Shah +1
We consider black-box optimization in which only an extremely limited number of function evaluations, on the order of around 100, are affordable and the function evaluations must b…