This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Abstract. Since problem solving in group problem-based learning is a collaborative process, modeling individuals and the group is necessary if we wish to develop an intelligent tut...