518 citations · 1.2k across the 27 of their papers we have counts for
32 papers
Spectral bandits
Tomáš Kocák, Rémi Munos, Branislav Kveton +2
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs of arms are smooth on a graph.…
Spectral Thompson sampling
Tomas Kocak, Michal Valko, Remi Munos +1
Thompson Sampling (TS) has attracted a lot of interest due to its good empirical performance, in particular in the computational advertising. Though successful, the tools for its p…
Dynamic Pricing and Advertising with Demand Learning
Shipra Agrawal, Yiding Feng, Wei Tang
We consider a novel pricing and advertising framework in which a seller not only sets the product price but also designs flexible advertising schemes to influence customers' valuat…
Online Allocation and Learning in the Presence of Strategic Agents
Steven Yin, Shipra Agrawal, Assaf Zeevi
We study the problem of allocating sequentially arriving items among homogeneous agents under the constraint that each agent must receive a pre-specified fraction of all it…
Scale Free Adversarial Multi Armed Bandits
Sudeep Raja Putta, Shipra Agrawal
We consider the Scale-Free Adversarial Multi Armed Bandits(MAB) problem. At the beginning of the game, the player only knows the number of arms . It does not know the scale and…
Dynamic Pricing and Learning under the Bass Model
Shipra Agrawal, Steven Yin, Assaf Zeevi
We consider a novel formulation of the dynamic pricing and demand learning problem, where the evolution of demand in response to posted prices is governed by a stochastic variant o…