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778views
15 years 5 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
WEBI
2005
Springer
14 years 1 months ago
A Novel Way of Computing Similarities between Nodes of a Graph, with Application to Collaborative Recommendation
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a M...
François Fouss, Alain Pirotte, Marco Saeren...
NAACL
2010
13 years 5 months ago
Automatic Domain Adaptation for Parsing
Current statistical parsers tend to perform well only on their training domain and nearby genres. While strong performance on a few related domains is sufficient for many situatio...
David McClosky, Eugene Charniak, Mark Johnson
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 11 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
ICCV
2005
IEEE
14 years 1 months ago
Object Categorization by Learned Universal Visual Dictionary
This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class mode...
John M. Winn, Antonio Criminisi, Thomas P. Minka