Inferential theory of learning

Known as: ITL, Inferential 
Inferential theory of learning (ITL) is an area of machine learning which describes inferential processes performed by learning agents. ITL has been… (More)
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Cybernetics
Machine learning

Papers overview

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Highly Cited
2007
Highly Cited
2007
ISP: Learning Inferential Selectional Preferences
Semantic inference is a key component for advanced natural language understanding. However, existing collections of automatically… (More)
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Highly Cited
2005
Highly Cited
2005
Inferential structure determination.
Macromolecular structures calculated from nuclear magnetic resonance data are not fully determined by experimental data but… (More)
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Highly Cited
2005
Highly Cited
2005
Query expansion using term relationships in language models for information retrieval
Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches… (More)
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2003
2003
Inferential Theory of Learning and Inductive Databases
ion Concretion Association Disassociation Similization Dissimilization Selection Generation Agglomeration Decomposition… (More)
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Highly Cited
2002
Highly Cited
2002
INFERENTIAL THEORY FOR FACTOR MODELS OF LARGE DIMENSIONS By
This paper develops an inferential theory for factor models of large dimensions. The principal components estimator is considered… (More)
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Highly Cited
2002
Highly Cited
2002
Larks: Dynamic Matchmaking Among Heterogeneous Software Agents in Cyberspace
Service matchmaking among heterogeneous software agents in the Internet is usually done dynamically and must be efficient. There… (More)
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Highly Cited
2001
Highly Cited
2001
Statistical applications of the multivariate skew-normal distribution
Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal… (More)
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Highly Cited
1999
Highly Cited
1999
Computational and Inferential Diiculties with Mixture Posterior Distributions 1
This paper deals with both exploration and interpretation problems related to posterior distributions for mixture models. The… (More)
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Highly Cited
1993
Highly Cited
1993
Inferential theory of learning as a conceptual basis for multistrategy learning
In view of a great proliferation of machine learning methods and paradigms, there is a need for a general conceptual framework… (More)
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Highly Cited
1992
Highly Cited
1992
Inferential Theory of Learning: Developing Foundations for Multistrategy Learning
The development of multistrategy learning systems should be based on a clear understanding of the roles and the applicability… (More)
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