We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Abstract. The high level of abstraction necessary to teach data structures and algorithmic schemes has been more than a hindrance to students. In order to make a proper approach to...
From some perspectives Automated Collaborative Filtering (ACF) appears quite similar to Case-Based Reasoning (CBR). It works on data organised around users and assets that might be...
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...