Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
In the single rent-to-buy decision problem, without a priori knowledge of the amount of time a resource will be used we need to decide when to buy the resource, given that we can ...
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
We consider the class of max-min and min-max optimization problems subject to a global budget (or weight) constraint and we undertake a systematic algorithmic and complexitytheore...
Deeparnab Chakrabarty, Aranyak Mehta, Vijay V. Vaz...