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TIP
2010
182views more  TIP 2010»
13 years 4 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
ESWS
2010
Springer
13 years 12 months ago
An Unsupervised Approach for Acquiring Ontologies and RDF Data from Online Life Science Databases
In the Linked Open Data cloud one of the largest data sets, comprising of 2.5 billion triples, is derived from the Life Science domain. Yet this represents a small fraction of the ...
Saqib Mir, Steffen Staab, Isabel Rojas
ICML
1996
IEEE
14 years 10 months ago
Unsupervised Learning Using MML
This paper discusses the unsupervised learning problem. An important part of the unsupervised learning problem is determining the numberofconstituent groups (componentsor classes)...
Jonathan J. Oliver, Rohan A. Baxter, Chris S. Wall...
ACL
2009
13 years 7 months ago
Distant supervision for relation extraction without labeled data
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...
Mike Mintz, Steven Bills, Rion Snow, Daniel Jurafs...
TSD
2007
Springer
14 years 4 months ago
On the Relative Hardness of Clustering Corpora
Abstract. Clustering is often considered the most important unsupervised learning problem and several clustering algorithms have been proposed over the years. Many of these algorit...
David Pinto, Paolo Rosso