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» Belief function independence: I. The marginal case
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NIPS
2003
13 years 8 months ago
Kernel Dimensionality Reduction for Supervised Learning
We propose a novel method of dimensionality reduction for supervised learning. Given a regression or classification problem in which we wish to predict a variable Y from an expla...
Kenji Fukumizu, Francis R. Bach, Michael I. Jordan
ATAL
2007
Springer
13 years 11 months ago
Model-based belief merging without distance measures
Merging operators try to define the beliefs of a group of agents according to the beliefs of each member of the group. Several model-based propositional belief merging operators h...
Verónica Borja Macías, Pilar Pozos P...
FLOPS
2006
Springer
13 years 11 months ago
Convergence in Language Design: A Case of Lightning Striking Four Times in the Same Place
What will a definitive programming language look like? By definitive language I mean a programming language that gives good soat its level of abstraction, allowing computer science...
Peter Van Roy
ASPDAC
2009
ACM
164views Hardware» more  ASPDAC 2009»
14 years 2 months ago
Accounting for non-linear dependence using function driven component analysis
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Lerong Cheng, Puneet Gupta, Lei He
BMCBI
2006
111views more  BMCBI 2006»
13 years 7 months ago
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
Background: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples...
Tomer Hertz, Chen Yanover