This paper formalizes Feature Selection as a Reinforcement Learning problem, leading to a provably optimal though intractable selection policy. As a second contribution, this pape...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
This paper provides guidance for operating an assemble-to-order system to maximize expected discounted profit, assuming that a high volume of prospective customers arrive per unit...
In this paper, we propose DBSampler, a query execution mechanism to answer "partial selection" queries in peerto-peer databases. A partial selection query is an arbitrar...
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...