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» Pattern statistics on Markov chains and sensitivity to param...
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JCNS
2010
104views more  JCNS 2010»
14 years 8 months ago
A new look at state-space models for neural data
State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely o...
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreir...
ANOR
2007
92views more  ANOR 2007»
14 years 9 months ago
Portfolio selection with probabilistic utility
We present a novel portfolio selection technique, which replaces the traditional maximization of the utility function with a probabilistic approach inspired by statistical physics....
Robert Marschinski, Pietro Rossi, Massimo Tavoni, ...
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
15 years 10 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
SSPR
2004
Springer
15 years 2 months ago
Adaptive Context for a Discrete Universal Denoiser
Abstract. Statistical analysis of spatially uniform signal contexts allows Discrete Universal Denoiser (DUDE) to effectively correct signal errors caused by a discrete symmetric me...
Georgy L. Gimel'farb
BMCBI
2006
102views more  BMCBI 2006»
14 years 9 months ago
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
Background: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algor...
Zafer Aydin, Yucel Altunbasak, Mark Borodovsky