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» Learning Causal Models of Relational Domains
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COLT
2010
Springer
13 years 7 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha
EKAW
2008
Springer
13 years 11 months ago
Learning Disjointness for Debugging Mappings between Lightweight Ontologies
Abstract. Dealing with heterogeneous ontologies by means of semantic mappings has become an important area of research and a number of systems for discovering mappings between onto...
Christian Meilicke, Johanna Völker, Heiner St...
CIKM
2009
Springer
14 years 2 months ago
An empirical study on using hidden markov model for search interface segmentation
This paper describes a hidden Markov model (HMM) based approach to perform search interface segmentation. Automatic processing of an interface is a must to access the invisible co...
Ritu Khare, Yuan An
IJCNN
2006
IEEE
14 years 3 months ago
A Self-Organising Map Approach for Clustering of XML Documents
— The number of XML documents produced and available on the Internet is steadily increasing. It is thus important to devise automatic procedures to extract useful information fro...
Francesca Trentini, Markus Hagenbuchner, Alessandr...
AAAI
1996
13 years 11 months ago
A Connectionist Framework for Reasoning: Reasoning with Examples
We present a connectionist architecture that supports almost instantaneous deductive and abductive reasoning. The deduction algorithm responds in few steps for single rule queries...
Dan Roth