A new method for function estimation and variable selection, specifically designed for additive models fitted by cubic splines is proposed.This new method involves regularizing ...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Abstract. We present a deterministic black box solution for online approximate matching. Given a pattern of length m and a streaming text of length n that arrives one character at ...
In this paper we consider a natural extension of the socalled reverse facility location problem which was introduced by Cabello et al. [3]. Given a set of n users and a set of m f...
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...