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Benchopt: Reproducible, efficient and collaborative optimization benchmarks. (arXiv:2206.13424v2 [cs.LG] UPDATED)
June 29, 2022, 1:11 a.m. | Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la
stat.ML updates on arXiv.org arxiv.org
Numerical validation is at the core of machine learning research as it allows
to assess the actual impact of new methods, and to confirm the agreement
between theory and practice. Yet, the rapid development of the field poses
several challenges: researchers are confronted with a profusion of methods to
compare, limited transparency and consensus on best practices, as well as
tedious re-implementation work. As a result, validation is often very partial,
which can lead to wrong conclusions that slow down …
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