We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
We study online pricing problems in markets with cancellations, i.e., markets in which prior allocation decisions can be revoked, but at a cost. In our model, a seller receives re...
Moshe Babaioff, Jason D. Hartline, Robert D. Klein...
We consider the polyhedral approach to solving the capacitated facility location problem. The valid inequalities considered are the knapsack, ow cover, e ective capacity, single d...
Abstract. We define a general concept of a network of analogue modules connected by channels, processing data from a metric space A, and operating with respect to a global continu...