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» Approximation Methods for Supervised Learning
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ICML
2010
IEEE
15 years 8 months ago
On the Consistency of Ranking Algorithms
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
John Duchi, Lester W. Mackey, Michael I. Jordan
194
Voted
ICML
2009
IEEE
16 years 8 months ago
Discriminative k-metrics
The k q-flats algorithm is a generalization of the popular k-means algorithm where q dimensional best fit affine sets replace centroids as the cluster prototypes. In this work, a ...
Arthur Szlam, Guillermo Sapiro
ICML
2007
IEEE
16 years 8 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
HCI
2007
15 years 8 months ago
OntoGen: Semi-automatic Ontology Editor
In this paper we present a semi-automatic ontology editor as implemented in a new version of OntoGen system. The system integrates machine learning and text mining algorithms into ...
Blaz Fortuna, Marko Grobelnik, Dunja Mladenic
187
Voted
IJON
2002
103views more  IJON 2002»
15 years 7 months ago
RBF networks training using a dual extended Kalman filter
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Iulian B. Ciocoiu