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» Learning a Continuous Hidden Variable Model for Binary Data
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DIS
2009
Springer
14 years 2 months ago
An Iterative Learning Algorithm for Within-Network Regression in the Transductive Setting
Within-network regression addresses the task of regression in partially labeled networked data where labels are sparse and continuous. Data for inference consist of entities associ...
Annalisa Appice, Michelangelo Ceci, Donato Malerba
UAI
2004
13 years 9 months ago
Dynamical Systems Trees
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
Andrew Howard, Tony Jebara
BMCBI
2005
302views more  BMCBI 2005»
13 years 7 months ago
CGHPRO - A comprehensive data analysis tool for array CGH
Background: Array CGH (Comparative Genomic Hybridisation) is a molecular cytogenetic technique for the genome wide detection of chromosomal imbalances. It is based on the cohybrid...
Wei Chen, Fikret Erdogan, H.-Hilger Ropers, Steffe...
NIPS
1998
13 years 9 months ago
An Entropic Estimator for Structure Discovery
We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
Matthew Brand
CORR
2010
Springer
183views Education» more  CORR 2010»
13 years 6 months ago
Discovering shared and individual latent structure in multiple time series
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
Suchi Saria, Daphne Koller, Anna Penn