We propose a novel 1 2-norm inverse solver for estimating the sources of EEG/MEG signals. Based on the standard 1-norm inverse solver, the proposed sparse distributed inverse solve...
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
A cost-sensitive extension of boosting, denoted as asymmetric boosting, is presented. Unlike previous proposals, the new algorithm is derived from sound decision-theoretic princip...
Performance of an application can be improved through augmenting the processor with Application specific Functional Units (AFUs). Usually a cluster of operations identified from th...
We consider a two-layer network algorithm. The first layer consists of an uncountable number of linear units. Each linear unit is an LMS algorithm whose inputs are first “kerne...