In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
A teaching methodology called Imitative-Reinforcement-Corrective (IRC) learning is described, and proposed as a general approach for teaching embodied non-linguistic AGI systems. I...
Ben Goertzel, Cassio Pennachin, Nil Geisweiller, M...
In multi-agent systems, individual problem solving capabilities can be improved thanks to the interaction with other agents. In the classification problem solving task each agent i...
Manual classification of free-text documents within a predefined hierarchy is highly time consuming. This is especially true for clinical guidelines, which are often indexed by mu...
Robert Moskovitch, Shiva Cohen-Kashi, Uzi Dror, If...