We study the adversarial multi-armed bandit problem, in which a player must iteratively make online decisions with linear loss vectors and hopes to achieve a small total loss. We consider a natural measure on the loss vectors, called deviation, which is the sum of the distances between every ...
Regret Analysis of Stochastic and Non-stochastic Multi-armed Bandit Problems, Sebastien Bubeck. 1 问题描述 在Adversarial bandit problem 中, 我们不再假设 reward 是从一个固定的分布中采样获得, 相反, 它由一个称为adversary 的 环境来决定. Adversarial bandit problem: ...
We study the multi-armed bandit problem with multiple plays and a budget constraint for both the stochastic and the adversarial setting. At each round, exactly $K$ out of $N$ possible arms have to be played (with $1\\leq K \\leq N$). In ... DP Zhou,CJ Tomlin 被引量: 9发表: ...
We consider the adversarial multi-armed bandit problem under delayed feedback. We analyze variants of the Exp3 algorithm that tune their step-size using only information (about the losses and delays) available at the time of the decisions, and obtain regret guarantees that adapt to the observed...
This is the adversarial problem. 这就是对抗性问题。 权威例句 Generative adversarial nets Generative Adversarial Nets Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA Gambling in a rigged casino: The adversarial multi-armed bandit problem ...
is the number of items and \(\Delta(i,j)\) is the gap between items \(i\) and \(j\). This indicates that the sleeping problem with preference feedback is inherently more difficult than that for classical multi-armed bandits (MAB). We then propose two algorithms, with near-optimal...
We study "adversarial scaling", a multi-armed bandit model where rewards have a stochastic and an adversarial component. Our model captures display advertising where the "click-through-rate" can be decomposed to a (fixed across time) arm-quality component and a non-stochastic user-relevance ...
We fill in a long open gap in the characterization of the minimax rate for the multi-armed bandit problem. Concretely, we remove an extraneous logarithmic factor in the previously known upper bound and propose a new family of randomized algorithms based on an implicit normalization, as well as...
Code Edit No code implementations yet. Submit your code now Tasks Edit Management Multi-Armed Bandits Datasets Edit Add Datasets introduced or used in this paper Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community ...
Est&Willow, CNRS/ENS/INRIA, Paris, Franceaudibert@certis.enpc.frSébastien BubeckSequeL Project, INRIA Lille40 avenue Halley,59650 Villeneuve d’Ascq, Francesebastien.bubeck@inria.frAbstractWe fill in a long open gap in the characterization ofthe minimax rate for the multi-armed bandit prob-lem....