261 citations · 1.4k across the 45 of their papers we have counts for
8 papers · 1 filter
Adversarial examples from computational constraints
Sébastien Bubeck, Eric Price, Ilya Razenshteyn
Why are classifiers in high dimension vulnerable to "adversarial" perturbations? We show that it is likely not due to information theoretic limitations, but rather it could be due…
Most Correlated Arms Identification
Che-Yu Liu, Sébastien Bubeck
We study the problem of finding the most mutually correlated arms among many arms. We show that adaptive arms sampling strategies can have significant advantages over the non-adapt…
lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits
Kevin Jamieson, Matthew Malloy, Robert Nowak +1
The paper proposes a novel upper confidence bound (UCB) procedure for identifying the arm with the largest mean in a multi-armed bandit game in the fixed confidence setting using a…
On Finding the Largest Mean Among Many
Kevin Jamieson, Matthew Malloy, Robert Nowak +1
Sampling from distributions to find the one with the largest mean arises in a broad range of applications, and it can be mathematically modeled as a multi-armed bandit problem in w…
Prior-free and prior-dependent regret bounds for Thompson Sampling
Sébastien Bubeck, Che-Yu Liu
We consider the stochastic multi-armed bandit problem with a prior distribution on the reward distributions. We are interested in studying prior-free and prior-dependent regret bou…
Bandits with heavy tail
Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
The stochastic multi-armed bandit problem is well understood when the reward distributions are sub-Gaussian. In this paper we examine the bandit problem under the weaker assumption…