Abstract-- This paper considers the problem of model reduction for controlled systems. The paper considers a dual/adjoint formulation of the general optimization problem to minimiz...
ABSTRACT. In this paper modified variants of the sparse Fourier transform algorithms from [14] are presented which improve on the approximation error bounds of the original algorit...
Abstract. In this paper we develop an algorithm for structured prediction that optimizes against complex performance measures, those which are a function of false positive and fals...
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly differe...