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PR
2007
104views more  PR 2007»
13 years 8 months ago
Optimizing resources in model selection for support vector machine
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
Mathias M. Adankon, Mohamed Cheriet
NIPS
2008
13 years 10 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
ECML
2000
Springer
14 years 1 months ago
Layered Learning
We examine how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compres...
Peter Stone, Manuela M. Veloso
MICCAI
2010
Springer
13 years 7 months ago
Spatially Regularized SVM for the Detection of Brain Areas Associated with Stroke Outcome
Abstract. This paper introduces a new method to detect group differences in brain images based on spatially regularized support vector machines (SVM). First, we propose to spatial...
Rémi Cuingnet, Charlotte Rosso, Stép...
EACL
2006
ACL Anthology
13 years 10 months ago
Automatic Acronym Recognition
This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym rec...
Dana Dannélls