1622 search results - page 147 / 325 » Learning a Hidden Matching |
135
Voted
GLVLSI
2005
IEEE
15 years 9 months ago
2005
IEEE
Switching model captures the data-driven uncertainty in logic circuits in a comprehensive probabilistic framework. Switching is a critical factor that influences dynamic, active ...
124
Voted
CORR
2010
Springer
2010
Springer
Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory
15 years 3 months ago
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
140
Voted
NECO
2010
15 years 1 months ago
2010
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
165
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ICML
2009
IEEE
16 years 4 months ago
2009
IEEE
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
118
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KDD
2009
ACM
16 years 4 months ago
2009
ACM
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...