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» Selectivity Estimation using Probabilistic Models
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AUSAI
2008
Springer
15 years 7 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe
162
Voted
AVBPA
2005
Springer
248views Biometrics» more  AVBPA 2005»
15 years 10 months ago
A New On-Line Model Quality Evaluation Method for Speaker Verification
The accurate selection of the utterances is very important to obtain right estimated speaker models in speaker verification. In this sense, it is important to determine the quality...
Javier R. Saeta, Javier Hernando
PAMI
2006
142views more  PAMI 2006»
15 years 4 months ago
Fingerprint Warping Using Ridge Curve Correspondences
The performance of a fingerprint matching system is affected by the nonlinear deformation introduced in the fingerprint impression during image acquisition. This nonlinear deformat...
Arun Ross, Sarat C. Dass, Anil K. Jain
180
Voted
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 8 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
JMLR
2002
137views more  JMLR 2002»
15 years 4 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