Preprint
Aug 2026
Online Algorithms via Minimax and Posterior Matching
Competitive analysis is central to the study of online algorithms, but upper bounds are often highly problem-specific. We develop a more unifying methodology via the minimax viewpoint. Guided by Yao's principle, we reduce worst-case competitive analysis to Bayesian online design under an arbitrary correlated prior over...
Thomas Kesselheim, Marco Molinaro, Kalen Patton et al.
· 1 citation