This paper gives a data structure (UDS) for supporting database retrieval, inference and machine learning that attempts to unify and extend previous work in relational databases, ...
In the context of machine learning from examples this paper deals with the problem of estimating the quality of attributes with and without dependencies among them. Kira and Rendel...
This paperpresents several industrial applications of MLin the context of their effort to solve the "KAMLproblem", i.e., the problem of merging knowledge acquisition and...
This paper describes a genetic learning system called SIA, which learns attributes based rules from a set of preclassified examples. Examples may be described with a variable numbe...
This paper addresses the problem of classifying observations when features are context-sensitive, specifically when the testing set involves a context that is different from the t...
Research in systems where learning is integrated to other components like problem solving, vision, or natural language is becoming an important topic for Machine Learning. Situatio...
Enric Plaza, Agnar Aamodt, Ashwin Ram, Walter Van ...
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...