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CSL
2008
Springer
13 years 7 months ago
A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on...
Andreas Vlachos
CIARP
2006
Springer
13 years 9 months ago
Robustness Analysis of the Neural Gas Learning Algorithm
The Neural Gas (NG) is a Vector Quantization technique where a set of prototypes self organize to represent the topology structure of the data. The learning algorithm of the Neural...
Carolina Saavedra, Sebastián Moreno, Rodrig...
CVPR
2009
IEEE
15 years 2 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
ICASSP
2010
IEEE
13 years 5 months ago
Speech enhancement with sparse coding in learned dictionaries
The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhan...
Christian D. Sigg, Tomas Dikk, Joachim M. Buhmann
CVPR
2010
IEEE
14 years 4 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...