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MTA
2006
173views more  MTA 2006»
15 years 7 months ago
Active learning in very large databases
Abstract. Query-by-example and query-by-keyword both suffer from the problem of "aliasing," meaning that example-images and keywords potentially have variable interpretat...
Navneet Panda, Kingshy Goh, Edward Y. Chang
JMLR
2002
137views more  JMLR 2002»
15 years 6 months ago
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
Masashi Sugiyama, Klaus-Robert Müller
ICIP
2008
IEEE
16 years 8 months ago
Learning structurally discriminant features in 3D faces
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
ICML
2010
IEEE
15 years 8 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
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IJCNN
2000
IEEE
15 years 11 months ago
A Neural Support Vector Network Architecture with Adaptive Kernels
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
Pascal Vincent, Yoshua Bengio