Know a great AI tool or AI news source? Submit it to AiByts
2 min read

Lower Bounds for Linear-Oracle Online Learning

Can a constant number of linear minimizations per round improve on the $T^{3/4}$ regret rate of online Frank-Wolfe on general convex sets? Weibel et al. conjectured that fixed-coefficient methods cannot.

By Mohit SinhaarXiv - stat.ML

Read the full story

Originally published by arXiv - stat.ML on Oct 1, 2026.

Read on arXiv - stat.ML(opens in a new tab)

Comments

Sign in to join the discussion.

No comments yet — be the first to share your thoughts.