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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 10 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 11 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»
16 years 7 days 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 5 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 11 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