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ICPR
2010
IEEE
15 years 11 months ago
A Bound on the Performance of LDA in Randomly Projected Data Spaces
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...
Robert John Durrant, Ata Kaban
AAAI
2012
13 years 6 months ago
Sparse Probabilistic Relational Projection
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
Wu-Jun Li, Dit-Yan Yeung
NIPS
2008
15 years 5 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
CORR
2007
Springer
164views Education» more  CORR 2007»
15 years 4 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach