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» Learning Algorithms for Domain Adaptation
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115
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ICML
2008
IEEE
16 years 1 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
KCAP
2005
ACM
15 years 6 months ago
Towards Browsing Distant Metadata Using Semantic Signatures
In this document, we describe a light-weighted ontology mediation method that allows users to send semantic queries to distant data repositories to browse for learning object meta...
Andrew Choi, Marek Hatala
119
Voted
IROS
2006
IEEE
113views Robotics» more  IROS 2006»
15 years 6 months ago
Policy Gradient Methods for Robotics
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
Jan Peters, Stefan Schaal
84
Voted
LREC
2010
196views Education» more  LREC 2010»
15 years 1 months ago
Ontology Based Law Discovery
The vast amount of information freely available on the Web constitutes a unparalleled resource for the automatic knoweledge discovery and learning. In this paper we propose a study...
Alessio Bosca, Luca Dini
ICIP
2009
IEEE
16 years 1 months ago
Physics-based Illuminant Color Estimation As An Image Semantics Clue
Most algorithms for extracting illuminant chromaticity from arbitrary images, such as the images found on the web, are based on machine learning techniques. We will show how a phy...