262 citations · 929 across the 33 of their papers we have counts for
5 papers · 1 filter
Bandits with Dynamic Arm-acquisition Costs
Anand Kalvit, Assaf Zeevi
We consider a bandit problem where at any time, the decision maker can add new arms to her consideration set. A new arm is queried at a cost from an "arm-reservoir" containing fini…
A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms
Anand Kalvit, Assaf Zeevi
One of the key drivers of complexity in the classical (stochastic) multi-armed bandit (MAB) problem is the difference between mean rewards in the top two arms, also known as the in…
From Finite to Countable-Armed Bandits
Anand Kalvit, Assaf Zeevi
We consider a stochastic bandit problem with countably many arms that belong to a finite set of types, each characterized by a unique mean reward. In addition, there is a fixed dis…
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…
Learning to Stop with Surprisingly Few Samples
Daniel Russo, Assaf Zeevi, Tianyi Zhang
We consider a discounted infinite horizon optimal stopping problem. If the underlying distribution is known a priori, the solution of this problem is obtained via dynamic programmi…