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PKDD
2009
Springer
170views Data Mining» more  PKDD 2009»
15 years 6 months ago
Statistical Relational Learning with Formal Ontologies
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
Achim Rettinger, Matthias Nickles, Volker Tresp
GRC
2010
IEEE
15 years 28 days ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
COLT
2005
Springer
15 years 5 months ago
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...
Mikhail Belkin, Partha Niyogi
MLDM
2005
Springer
15 years 5 months ago
Clustering Large Dynamic Datasets Using Exemplar Points
In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. The approach is based on the dynamic representation of clus...
William Sia, Mihai M. Lazarescu
KDD
2012
ACM
254views Data Mining» more  KDD 2012»
13 years 2 months ago
Playlist prediction via metric embedding
Digital storage of personal music collections and cloud-based music services (e.g. Pandora, Spotify) have fundamentally changed how music is consumed. In particular, automatically...
Shuo Chen, Josh L. Moore, Douglas Turnbull, Thorst...