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ECML
2003
Springer
14 years 25 days ago
Optimizing Local Probability Models for Statistical Parsing
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems â€...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
PAMI
2011
12 years 10 months ago
Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...
Yang Wang 0003, Greg Mori
ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 7 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ISI
2008
Springer
13 years 7 months ago
Probabilistic frameworks for privacy-aware data mining
Often several cooperating parties would like to have a global view of their joint data for various data mining objectives, but cannot reveal the contents of individual records due...
Joydeep Ghosh
PPSN
2004
Springer
14 years 29 days ago
Learning Probabilistic Tree Grammars for Genetic Programming
Genetic Programming (GP) provides evolutionary methods for problems with tree representations. A recent development in Genetic Algorithms (GAs) has led to principled algorithms cal...
Peter A. N. Bosman, Edwin D. de Jong