5 papers
When Sparsity Breaks Connectivity: Functional Reachability and Guided Topology Dynamics in Extreme Sparse Training
Mohammad Pasande, Mateusz Jaworski, Jeroen Rook +1
Dynamic Sparse Training (DST) periodically prunes and regrows connections, inducing a discrete dynamical mechanism over network topologies. At extreme sparsity (), this d…
Exploration of Pareto-preserving Search Space Transformations in Multi-objective Test Functions
Diederick Vermetten, Jeroen Rook
Benchmark problems are an important tool for gaining understanding of optimization algorithms. Since algorithms often aim to perform well on benchmarks, biases in benchmark design…
MO-ELA: Rigorously Expanding Exploratory Landscape Features for Automated Algorithm Selection in Continuous Multi-Objective Optimisation
Oliver Preuß, Jeroen Rook, Jakob Bossek +1
Automated Algorithm Selection (AAS) is a popular meta-algorithmic approach and has demonstrated to work well for single-objective optimisation in combination with exploratory lands…
Benchmarking that Matters: Rethinking Benchmarking for Practical Impact
Anna V. Kononova, Niki van Stein, Olaf Mersmann +14
Benchmarking has driven scientific progress in Evolutionary Computation, yet current practices fall short of real-world needs. Widely used synthetic suites such as BBOB and CEC iso…
MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler
Diederick Vermetten, Jeroen Rook, Oliver L. Preuß +5
Benchmarking is one of the key ways in which we can gain insight into the strengths and weaknesses of optimization algorithms. In sampling-based optimization, considering the anyti…