106 citations · 996 across the 72 of their papers we have counts for
5 papers · 1 filter
Corralling a Band of Bandit Algorithms
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur +1
We study the problem of combining multiple bandit algorithms (that is, online learning algorithms with partial feedback) with the goal of creating a master algorithm that performs…
Oracle-Efficient Online Learning and Auction Design
Miroslav Dudík, Nika Haghtalab, Haipeng Luo +3
We consider the design of computationally efficient online learning algorithms in an adversarial setting in which the learner has access to an offline optimization oracle. We prese…
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits
Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy +1
We give an oracle-based algorithm for the adversarial contextual bandit problem, where either contexts are drawn i.i.d. or the sequence of contexts is known a priori, but where the…
Efficient Second Order Online Learning by Sketching
Haipeng Luo, Alekh Agarwal, Nicolo Cesa-Bianchi +1
We propose Sketched Online Newton (SON), an online second order learning algorithm that enjoys substantially improved regret guarantees for ill-conditioned data. SON is an enhanced…
Variance-Reduced and Projection-Free Stochastic Optimization
Elad Hazan, Haipeng Luo
The Frank-Wolfe optimization algorithm has recently regained popularity for machine learning applications due to its projection-free property and its ability to handle structured c…