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ICASSP
2011
IEEE
14 years 8 months ago
A new stochastic image model based on Markov random fields and its application to texture modeling
Stochastic image modeling based on conventional Markov random fields is extensively discussed in the literature. A new stochastic image model based on Markov random fields is intr...
Siamak Yousefi, Nasser D. Kehtarnavaz
CORR
2007
Springer
169views Education» more  CORR 2007»
15 years 4 months ago
Algorithmic Complexity Bounds on Future Prediction Errors
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true d...
Alexey V. Chernov, Marcus Hutter, Jürgen Schm...
ICCS
2004
Springer
15 years 10 months ago
The Computational Complexity of Orientation Search in Cryo-Electron Microscopy
Abstract. In this paper we study the problem of determining threedimensional orientations for noisy projections of randomly oriented identical particles. The problem is of central ...
Taneli Mielikäinen, Janne Ravantti, Esko Ukko...
JSYML
2006
86views more  JSYML 2006»
15 years 4 months ago
Degrees of monotone complexity
Levin and Schnorr (independently) introduced the monotone complexity, Km(), of a binary string . We use monotone complexity to define the relative complexity (or relative randomnes...
William C. Calhoun
134
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IBPRIA
2007
Springer
15 years 8 months ago
Random Forest for Gene Expression Based Cancer Classification: Overlooked Issues
Random forest is a collection (ensemble) of decision trees. It is a popular ensemble technique in pattern recognition. In this article, we apply random forest for cancer classifica...
Oleg Okun, Helen Priisalu