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» Approximation Methods for Supervised Learning
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ICML
2007
IEEE
14 years 10 months ago
Discriminative Gaussian process latent variable model for classification
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
Raquel Urtasun, Trevor Darrell
JMLR
2010
186views more  JMLR 2010»
13 years 4 months ago
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
Philippos Mordohai, Gérard G. Medioni
IJISTA
2007
101views more  IJISTA 2007»
13 years 10 months ago
Incremental online PCA for automatic motion learning of eigen behaviour
: This paper presents an online learning framework for the behavior of an articulated body by capturing its motion using real-time video. In our proposed framework, supervised lear...
Xianhua Jiang, Yuichi Motai
ISMIS
2009
Springer
14 years 4 months ago
Fuzzy Clustering for Categorical Spaces
Abstract. A multi-relational clustering method is presented which can be applied to complex knowledge bases storing resources expressed in the standard Semantic Web languages. It a...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
ICML
2006
IEEE
14 years 10 months ago
Practical solutions to the problem of diagonal dominance in kernel document clustering
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...
Derek Greene, Padraig Cunningham