91 citations · 526 across the 50 of their papers we have counts for
14 papers · 1 filter
Automated Dynamic Algorithm Configuration
Steven Adriaensen, André Biedenkapp, Gresa Shala +4
The performance of an algorithm often critically depends on its parameter configuration. While a variety of automated algorithm configuration methods have been proposed to relieve…
DACBench: A Benchmark Library for Dynamic Algorithm Configuration
Theresa Eimer, André Biedenkapp, Maximilian Reimer +3
Dynamic Algorithm Configuration (DAC) aims to dynamically control a target algorithm's hyperparameters in order to improve its performance. Several theoretical and empirical result…
Neural Model-based Optimization with Right-Censored Observations
Katharina Eggensperger, Kai Haase, Philipp Müller +2
In many fields of study, we only observe lower bounds on the true response value of some experiments. When fitting a regression model to predict the distribution of the outcomes, w…
Learning Heuristic Selection with Dynamic Algorithm Configuration
David Speck, André Biedenkapp, Frank Hutter +2
A key challenge in satisficing planning is to use multiple heuristics within one heuristic search. An aggregation of multiple heuristic estimates, for example by taking the maximum…
The Algorithm Selection Competitions 2015 and 2017
Marius Lindauer, Jan N. van Rijn, Lars Kotthoff
The algorithm selection problem is to choose the most suitable algorithm for solving a given problem instance. It leverages the complementarity between different approaches that is…
Neural Networks for Predicting Algorithm Runtime Distributions
Katharina Eggensperger, Marius Lindauer, Frank Hutter
Many state-of-the-art algorithms for solving hard combinatorial problems in artificial intelligence (AI) include elements of stochasticity that lead to high variations in runtime,…
Warmstarting of Model-based Algorithm Configuration
Marius Lindauer, Frank Hutter
The performance of many hard combinatorial problem solvers depends strongly on their parameter settings, and since manual parameter tuning is both tedious and suboptimal the AI com…
Pitfalls and Best Practices in Algorithm Configuration
Katharina Eggensperger, Marius Lindauer, Frank Hutter
Good parameter settings are crucial to achieve high performance in many areas of artificial intelligence (AI), such as propositional satisfiability solving, AI planning, scheduling…
Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates
Katharina Eggensperger, Marius Lindauer, Holger H. Hoos +2
The optimization of algorithm (hyper-)parameters is crucial for achieving peak performance across a wide range of domains, ranging from deep neural networks to solvers for hard com…
A case study of algorithm selection for the traveling thief problem
Markus Wagner, Marius Lindauer, Mustafa Misir +2
Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013…
ASlib: A Benchmark Library for Algorithm Selection
Bernd Bischl, Pascal Kerschke, Lars Kotthoff +8
The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set…
The Configurable SAT Solver Challenge (CSSC)
Frank Hutter, Marius Lindauer, Adrian Balint +3
It is well known that different solution strategies work well for different types of instances of hard combinatorial problems. As a consequence, most solvers for the propositional…
claspfolio 2: Advances in Algorithm Selection for Answer Set Programming
Holger Hoos, Marius Lindauer, Torsten Schaub
To appear in Theory and Practice of Logic Programming (TPLP). Building on the award-winning, portfolio-based ASP solver claspfolio, we present claspfolio 2, a modular and open solv…
Solver Scheduling via Answer Set Programming
Holger Hoos, Roland Kaminski, Marius Lindauer +1
Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different ty…