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NIPS
2004
15 years 8 months ago
Modelling Uncertainty in the Game of Go
Go is an ancient oriental game whose complexity has defeated attempts to automate it. We suggest using probability in a Bayesian sense to model the uncertainty arising from the va...
David H. Stern, Thore Graepel, David J. C. MacKay
IWCLS
2007
Springer
16 years 20 days ago
A Principled Foundation for LCS
In this paper we explicitly identify the probabilistic model underlying LCS by linking it to a generalisation of the common Mixture-of-Experts model. Having an explicit representa...
Jan Drugowitsch, Alwyn Barry
NIPS
2008
15 years 8 months ago
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Shay B. Cohen, Kevin Gimpel, Noah A. Smith
ICIP
2001
IEEE
16 years 8 months ago
Supervised segmentation and tracking of nonrigid objects using a "mixture of histograms" model
Segmentation and tracking of objects in video sequences is important for a number of applications. In the supervised variant, segmentation can be achieved by modelling the probabi...
Mark Everingham, Barry T. Thomas
ECCV
1994
Springer
15 years 10 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li