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» Prediction on Spike Data Using Kernel Algorithms
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CORR
2006
Springer
76views Education» more  CORR 2006»
15 years 6 months ago
Inconsistent parameter estimation in Markov random fields: Benefits in the computation-limited setting
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
Martin J. Wainwright
DMIN
2009
136views Data Mining» more  DMIN 2009»
15 years 4 months ago
Evaluating Algorithms for Concept Description
When performing concept description, models need to be evaluated both on accuracy and comprehensibility. A comprehensible concept description model should present the most importan...
Cecilia Sönströd, Ulf Johansson, Tuve L&...
BMCBI
2010
167views more  BMCBI 2010»
15 years 6 months ago
Inference of sparse combinatorial-control networks from gene-expression data: a message passing approach
Background: Transcriptional gene regulation is one of the most important mechanisms in controlling many essential cellular processes, including cell development, cell-cycle contro...
Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pag...
MICCAI
2009
Springer
16 years 7 months ago
Think Global, Act Local; Projectome Estimation with BlueMatter
Estimating the complete set of white matter fascicles (the projectome) from diffusion data requires evaluating an enormous number of potential pathways; consequently, most algorith...
Anthony Sherbondy, Robert Dougherty, Rajagopal A...
CVPR
2006
IEEE
16 years 8 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...