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» Learning Functions from Imperfect Positive Data
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BMCBI
2007
157views more  BMCBI 2007»
13 years 7 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
RECOMB
2007
Springer
14 years 8 months ago
Minimizing and Learning Energy Functions for Side-Chain Prediction
Abstract. Side-chain prediction is an important subproblem of the general protein folding problem. Despite much progress in side-chain prediction, performance is far from satisfact...
Chen Yanover, Ora Schueler-Furman, Yair Weiss
ML
2002
ACM
100views Machine Learning» more  ML 2002»
13 years 7 months ago
Structure in the Space of Value Functions
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
David J. Foster, Peter Dayan
NIPS
1990
13 years 8 months ago
Bumptrees for Efficient Function, Constraint and Classification Learning
A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. A...
Stephen M. Omohundro
CORR
2010
Springer
138views Education» more  CORR 2010»
13 years 4 months ago
Rules of Thumb for Information Acquisition from Large and Redundant Data
We develop an abstract model of information acquisition from redundant data. We assume a random sampling process from data which contain information with bias and are interested in...
Wolfgang Gatterbauer