Performance2vec
Tome Eftimov, Gorjan Popovski, Dragi Kocev, Peter Korošec · 2020
When working on a new stochastic optimization algorithm, one task that should be performed is to compare its performance with those of state-of-the-art algorithms. The literature suggests that the most commonly applied approaches for comparing algorithms' performances use statistical analyses. However, to provide a more meaningful explanation about algorithms' performances, we propose a methodology, named performance2vec, which computes a vector representation of each algorithm's performance by embedding it in some performance space determined by a set of benchmark problems. Experimental results show that the proposed embeddings, paired with clustering approaches, provide a more in-depth explanation regarding the algorithms' performance by exploring the relations between them and the benchmark problems.