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» Probabilistic Justification and the Regress Problem
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IPSN
2005
Springer
14 years 29 days ago
A robust architecture for distributed inference in sensor networks
— Many inference problems that arise in sensor networks require the computation of a global conclusion that is consistent with local information known to each node. A large class...
Mark A. Paskin, Carlos Guestrin, Jim McFadden
ISCI
2008
137views more  ISCI 2008»
13 years 7 months ago
Stochastic dominance-based rough set model for ordinal classification
In order to discover interesting patterns and dependencies in data, an approach based on rough set theory can be used. In particular, Dominance-based Rough Set Approach (DRSA) has...
Wojciech Kotlowski, Krzysztof Dembczynski, Salvato...
SIGIR
2008
ACM
13 years 7 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum

Book
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...
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
14 years 1 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...