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» On Sequence Prediction for Arbitrary Measures
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ICIP
2008
IEEE
14 years 2 months ago
General region merging approaches based on information theory statistical measures
This work presents a new statistical approach to region merging where regions are modeled as arbitrary discrete distributions, directly estimated from the pixel values. Under this...
Felipe Calderero, Ferran Marqués
FLAIRS
2008
13 years 10 months ago
Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
Mehdi Manshadi, Reid Swanson, Andrew S. Gordon
WWW
2008
ACM
14 years 8 months ago
Web page rank prediction with markov models
In this paper we propose a method for predicting the ranking position of a Web page. Assuming a set of successive past top-k rankings, we study the evolution of Web pages in terms...
Michalis Vazirgiannis, Dimitris Drosos, Pierre Sen...
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
JMLR
2010
92views more  JMLR 2010»
13 years 2 months ago
Posterior distributions are computable from predictive distributions
As we devise more complicated prior distributions, will inference algorithms keep up? We highlight a negative result in computable probability theory by Ackerman, Freer, and Roy (...
Cameron E. Freer, Daniel M. Roy