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» Prediction on Spike Data Using Kernel Algorithms
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125
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CORR
2006
Springer
76views Education» more  CORR 2006»
15 years 2 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
144
Voted
DMIN
2009
136views Data Mining» more  DMIN 2009»
15 years 9 days 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 2 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 3 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...
143
Voted
CVPR
2006
IEEE
16 years 4 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...