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» Core Vector Regression for very large regression problems
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ENTCS
2002
72views more  ENTCS 2002»
13 years 7 months ago
A Symbolic Out-of-Core Solution Method for Markov Models
Despite considerable effort, the state-space explosion problem remains an issue in the analysis of Markov models. Given structure, symbolic representations can result in very comp...
Marta Z. Kwiatkowska, Rashid Mehmood, Gethin Norma...
NIPS
2008
13 years 9 months ago
Generative versus discriminative training of RBMs for classification of fMRI images
Neuroimaging datasets often have a very large number of voxels and a very small number of training cases, which means that overfitting of models for this data can become a very se...
Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel...
SIGIR
2004
ACM
14 years 1 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
COLT
2007
Springer
13 years 11 months ago
Robust Reductions from Ranking to Classification
Abstract. We reduce ranking, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC), to binary classification. The core theorem shows that a binary classif...
Maria-Florina Balcan, Nikhil Bansal, Alina Beygelz...
NIPS
2000
13 years 9 months ago
Vicinal Risk Minimization
The Vicinal Risk Minimization principle establishes a bridge between generative models and methods derived from the Structural Risk Minimization Principle such as Support Vector M...
Olivier Chapelle, Jason Weston, Léon Bottou...