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ICPR
2006
IEEE
14 years 8 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum
UAI
2000
13 years 8 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
SIGMOD
2008
ACM
169views Database» more  SIGMOD 2008»
14 years 7 months ago
MCDB: a monte carlo approach to managing uncertain data
To deal with data uncertainty, existing probabilistic database systems augment tuples with attribute-level or tuple-level probability values, which are loaded into the database al...
Ravi Jampani, Fei Xu, Mingxi Wu, Luis Leopoldo Per...
ICFEM
2004
Springer
14 years 25 days ago
Linear Inequality LTL (iLTL): A Model Checker for Discrete Time Markov Chains
Abstract. We develop a way of analyzing the behavior of systems modeled using Discrete Time Markov Chains (DTMC). Specifically, we define iLTL, an LTL with linear inequalities on...
YoungMin Kwon, Gul Agha
TMI
2010
182views more  TMI 2010»
13 years 5 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern