85 citations · 897 across the 89 of their papers we have counts for
16 papers · 1 filter
Squirrel: A Switching Hyperparameter Optimizer
Noor Awad, Gresa Shala, Difan Deng +9
In this short note, we describe our submission to the NeurIPS 2020 BBO challenge. Motivated by the fact that different optimizers work well on different problems, our approach swit…
Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking
Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong +5
Existing studies in black-box optimization for machine learning suffer from low generalizability, caused by a typically selective choice of problem instances used for training and…
Linear Matrix Factorization Embeddings for Single-objective Optimization Landscapes
Tome Eftimov, Gorjan Popovski, Quentin Renau +2
Automated per-instance algorithm selection and configuration have shown promising performances for a number of classic optimization problems, including satisfiability, AI planning,…
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis
Elena Raponi, Hao Wang, Mariusz Bujny +2
Bayesian Optimization (BO) is a surrogate-assisted global optimization technique that has been successfully applied in various fields, e.g., automated machine learning and design o…
IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics
Hao Wang, Diederick Vermetten, Furong Ye +2
Benchmarking and performance analysis play an important role in understanding the behaviour of iterative optimization heuristics (IOHs) such as local search algorithms, genetic and…
Benchmarking in Optimization: Best Practice and Open Issues
Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg +14
This survey compiles ideas and recommendations from more than a dozen researchers with different backgrounds and from different institutes around the world. Promoting best practice…