In this paper we propose a novel general framework for unsupervised model adaptation. Our method is based on entropy which has been used previously as a regularizer in semi-superv...
Ariya Rastrow, Frederick Jelinek, Abhinav Sethy, B...
In the paper we present a new evolutionary algorithm for induction of regression trees. In contrast to the typical top-down approaches it globally searches for the best tree struct...
The electrical activity of the heart may be modeled by a non-linear system of partial differential equations known as the bidomain model. Due to the rapid variations in the electr...
A smoothing finite impulse response (FIR) filter is addressed for discrete time-invariant state-space polynomial models commonly used to model signals over finite data. A gener...
Oscar Gerardo Ibarra-Manzano, Yuriy S. Shmaliy, Lu...
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa