57 citations · 72 across the 5 of their papers we have counts for
4 papers · 1 filter
Near-optimal method for highly smooth convex optimization
Sébastien Bubeck, Qijia Jiang, Yin Tat Lee +2
We propose a near-optimal method for highly smooth convex optimization. More precisely, in the oracle model where one obtains the order Taylor expansion of a function at t…
Competitively Chasing Convex Bodies
Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li +1
Let be a family of sets in some metric space. In the -chasing problem, an online algorithm observes a request sequence of sets in and respo…
Chasing Nested Convex Bodies Nearly Optimally
Sébastien Bubeck, Bo'az Klartag, Yin Tat Lee +2
The convex body chasing problem, introduced by Friedman and Linial, is a competitive analysis problem on any normed vector space. In convex body chasing, for each timestep $t\in\ma…
Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits
Zeyuan Allen-Zhu, Sébastien Bubeck, Yuanzhi Li
Regret bounds in online learning compare the player's performance to , the optimal performance in hindsight with a fixed strategy. Typically such bounds scale with the square…