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» Approximate Inference and Constrained Optimization
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CVPR
2007
IEEE
14 years 9 months ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
COGSCI
2008
74views more  COGSCI 2008»
13 years 7 months ago
Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?
Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were ...
Michael C. Mozer, Harold Pashler, Hadjar Homaei
ICCV
2005
IEEE
14 years 1 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
BMCBI
2005
115views more  BMCBI 2005»
13 years 7 months ago
Statistical distributions of optimal global alignment scores of random protein sequences
Background: The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function un...
Hongxia Pang, Jiaowei Tang, Su-Shing Chen, Shiheng...
JAIR
1998
81views more  JAIR 1998»
13 years 7 months ago
Computational Aspects of Reordering Plans
This article studies the problem of modifying the action ordering of a plan in order to optimise the plan according to various criteria. One of these criteria is to make a plan le...
Christer Bäckström