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BMCBI
2008
128views more  BMCBI 2008»
13 years 10 months ago
Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor bindin
Background: Biologically active sequence motifs often have positional preferences with respect to a genomic landmark. For example, many known transcription factor binding sites (T...
Nak-Kyeong Kim, Kannan Tharakaraman, Leonardo Mari...
TIT
1998
96views more  TIT 1998»
13 years 9 months ago
Sequential Prediction of Individual Sequences Under General Loss Functions
Abstract— We consider adaptive sequential prediction of arbitrary binary sequences when the performance is evaluated using a general loss function. The goal is to predict on each...
David Haussler, Jyrki Kivinen, Manfred K. Warmuth
TNN
1998
114views more  TNN 1998»
13 years 9 months ago
Bayesian retrieval in associative memories with storage errors
Abstract—It is well known that for finite-sized networks, onestep retrieval in the autoassociative Willshaw net is a suboptimal way to extract the information stored in the syna...
Friedrich T. Sommer, Peter Dayan
EWC
2010
178views more  EWC 2010»
13 years 7 months ago
Design of tensegrity structures using parametric analysis and stochastic search
Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, findin...
Landolf Rhode-Barbarigos, Himanshu Jain, Prakash K...
ECCV
2002
Springer
14 years 11 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu