We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
We provide a novel view of learning an approximate model of a partially observable environment from data and present a simple implemenf the idea. The learned model abstracts away ...
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Motivation: Sigma factors regulate the expression of genes in Bacillus subtilis at the transcriptional level. First we assess the ability of currently available gene regulatory ne...
Michiel J. L. de Hoon, Yuko Makita, Seiya Imoto, K...