AI RESEARCH

Pareto-Optimal Anytime Algorithms via Bayesian Racing

arXiv CS.LG

ArXi:2603.08493v1 Announce Type: cross Selecting an optimization algorithm requires comparing candidates across problem instances, but the computational budget for deployment is often unknown at benchmarking time. Current methods either collapse anytime performance into a scalar, require manual interpretation of plots, or produce