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175
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UAI
2004
15 years 7 months ago
Bayesian Learning in Undirected Graphical Models: Approximate MCMC Algorithms
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Iain Murray, Zoubin Ghahramani
CMOT
2000
94views more  CMOT 2000»
15 years 6 months ago
Performance of Organizational Design Models and Their Impact on Organization Learning
Theperformanceofvariousorganizationalstructuresisanessentialparameterinthereengineeringoforganizations, particularly in the current rapidly changing, competitive and information t...
Aris M. Ouksel, Ronald Vyhmeister
MICCAI
2010
Springer
15 years 4 months ago
Agreement-Based Semi-supervised Learning for Skull Stripping
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
272
Voted
AR
2011
15 years 1 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
ICML
2009
IEEE
16 years 7 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever