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ICML
2009
IEEE
16 years 3 months ago
Compositional noisy-logical learning
We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
Alan L. Yuille, Songfeng Zheng
CORR
2006
Springer
99views Education» more  CORR 2006»
15 years 3 months ago
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
ECTEL
2007
Springer
15 years 9 months ago
An Interoperability Infrastructure for Distributed Feed Networks
Blogs have the aordance to become an integral part of teaching and learning processes as a vehicle for knowledge management. Open, exible systems integrating blogs provide user-f...
Fridolin Wild, Steinn E. Sigurðarson, Stefan S...
NN
2006
Springer
163views Neural Networks» more  NN 2006»
15 years 2 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
JMLR
2006
103views more  JMLR 2006»
15 years 3 months ago
MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals
In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Dana Pe'er, Amos Tanay, Aviv Regev