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JMLR
2010
123views more  JMLR 2010»
13 years 3 months ago
Inductive Principles for Restricted Boltzmann Machine Learning
Recent research has seen the proposal of several new inductive principles designed specifically to avoid the problems associated with maximum likelihood learning in models with in...
Benjamin Marlin, Kevin Swersky, Bo Chen, Nando de ...
CSDA
2007
94views more  CSDA 2007»
13 years 8 months ago
Some extensions of score matching
Many probabilistic models are only defined up to a normalization constant. This makes maximum likelihood estimation of the model parameters very difficult. Typically, one then h...
Aapo Hyvärinen
DAGM
2004
Springer
14 years 1 months ago
A Probabilistic Framework for Robust and Accurate Matching of Point Clouds
We present a probabilistic framework for matching of point clouds. Variants of the ICP algorithm typically pair points to points or points to lines. Instead, we pair data points to...
Peter Biber, Sven Fleck, Wolfgang Straßer
AAAI
2006
13 years 10 months ago
Inexact Matching of Ontology Graphs Using Expectation-Maximization
We present a new method for mapping ontology schemas that address similar domains. The problem of ontology mapping is crucial since we are witnessing a decentralized development a...
Prashant Doshi, Christopher Thomas
DAGM
2004
Springer
14 years 1 months ago
A Higher Order MRF-Model for Stereo-Reconstruction
Abstract. We consider the task of stereo-reconstruction under the following fairly broad assumptions. A single and continuously shaped object is captured by two uncalibrated camera...
Dmitrij Schlesinger, Boris Flach, Alexander Shekho...