A framework for analyzing the computational capabilities and the limitations of the evolutionary process of random change guided by selection was recently introduced by Valiant [V...
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
Background: Computational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remain...
Yuko Makita, Michiel J. L. de Hoon, Antoine Danchi...
When comparing discrete probability distributions, natural measures of similarity are not p distances but rather are informationdivergences such as Kullback-Leibler and Hellinger. ...
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...