Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Aiming to clarify the convergence or divergence conditions for Learning Classifier System (LCS), this paper explores: (1) an extreme condition where the reinforcement process of ...
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...
We consider the least-square linear regression problem with regularization by the 1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot...