We address well-studied problems concerning the learnability of parities and halfspaces in the presence of classification noise. Learning of parities under the uniform distributi...
In this paper, starting from the limitations and constrains of traditional human learning approaches, we outline new suitable approaches to education and training in future knowle...
Angelo Gaeta, Pierluigi Ritrovato, Francesco Orciu...
Automated agents for electricity markets, social networks, and other distributed networks must repeatedly interact with other intelligent agents, often without observing associate...
Jacob W. Crandall, Asad Ahmed, Michael A. Goodrich
Bayes statistics and statistical physics have the common mathematical structure, where the log likelihood function corresponds to the random Hamiltonian. Recently, it was discovere...
In the CLear project we develop a cooperative learning system for supporting learning and training processes of co-located and distributed groups. One of the fundamental concepts o...