Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
The aim of this paper is to propose a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to est...
The work described is part of an ongoing interdisciplinary collaboration between two research teams of the University of Patras, Greece and the University of Freiburg, Germany, whi...
Georgios Kahrimanis, Anne Meier, Irene-Angelica Ch...
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...