19 citations · 27 across the 8 of their papers we have counts for
5 papers · 1 filter
A second order regret bound for NormalHedge
Yoav Freund, Nicholas J. A. Harvey, Victor S. Portella +2
We consider the problem of prediction with expert advice for ``easy'' sequences. We show that a variant of NormalHedge enjoys a second-order -quantile regret bound of $O\big(\sq…
Continuous Prediction with Experts' Advice
Victor Sanches Portella, Christopher Liaw, Nicholas J. A. Harvey
Prediction with experts' advice is one of the most fundamental problems in online learning and captures many of its technical challenges. A recent line of work has looked at online…
Efficient and Optimal Fixed-Time Regret with Two Experts
Laura Greenstreet, Nicholas J. A. Harvey, Victor Sanches Portella
Prediction with expert advice is a foundational problem in online learning. In instances with rounds and experts, the classical Multiplicative Weights Update method suffers…
Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses
Yihan Zhou, Victor S. Portella, Mark Schmidt +1
In online convex optimization (OCO), Lipschitz continuity of the functions is commonly assumed in order to obtain sublinear regret. Moreover, many algorithms have only logarithmic…
Online mirror descent and dual averaging: keeping pace in the dynamic case
Huang Fang, Nicholas J. A. Harvey, Victor S. Portella +1
Online mirror descent (OMD) and dual averaging (DA) -- two fundamental algorithms for online convex optimization -- are known to have very similar (and sometimes identical) perform…