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» Variational methods for Reinforcement Learning
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ECCV
2010
Springer
13 years 10 months ago
Clustering Complex Data with Group-Dependent Feature Selection
Abstract. We describe a clustering approach with the emphasis on detecting coherent structures in a complex dataset, and illustrate its effectiveness with computer vision applicat...
JMLR
2008
159views more  JMLR 2008»
13 years 7 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
PAMI
2006
128views more  PAMI 2006»
13 years 7 months ago
On Weighting Clustering
Recent papers and patents in iterative unsupervised learning have emphasized a new trend in clustering. It basically consists of penalizing solutions via weights on the instance po...
Richard Nock, Frank Nielsen
CSCW
2002
ACM
13 years 7 months ago
Voice-mail diary studies for naturalistic data capture under mobile conditions
Mobile technology requires new methods for studying its use under realistic conditions "in the field." Reflexively, mobile technology also creates new opportunities for ...
Leysia Palen, Marilyn C. Salzman
PR
2007
81views more  PR 2007»
13 years 7 months ago
Graph embedding using tree edit-union
In this paper we address the problem of how to learn a structural prototype that can be used to represent the variations present in a set of trees. The prototype serves as a patte...
Andrea Torsello, Edwin R. Hancock