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PAKM
2008
13 years 9 months ago
Classifying Digital Resources in a Practical and Coherent Way with Easy-to-Get Features
With a rich variety of forms and types, digital resources are complex data objects. They grows fast in volume on the Web, but hard to be classified efficiently. The paper presents ...
Chong Chen, Hongfei Yan, Xiaoming Li
ICML
2010
IEEE
13 years 8 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
ICMCS
2006
IEEE
173views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Applying Supervised Classifiers Based on Non-negative Matrix Factorization to Musical Instrument Classification
In this paper, a new approach for automatic audio classification using non-negative matrix factorization (NMF) is presented. Training is performed onto each audio class individua...
Emmanouil Benetos, Margarita Kotti, Constantine Ko...
ICDAR
2007
IEEE
14 years 1 months ago
Fast Lexicon-Based Scene Text Recognition with Sparse Belief Propagation
Using a lexicon can often improve character recognition under challenging conditions, such as poor image quality or unusual fonts. We propose a flexible probabilistic model for c...
Jerod J. Weinman, Erik G. Learned-Miller, Allen R....
GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
13 years 11 months ago
A Bayesian approach to learning classifier systems in uncertain environments
In this paper we propose a Bayesian framework for XCS [9], called BXCS. Following [4], we use probability distributions to represent the uncertainty over the classifier estimates ...
Davide Aliprandi, Alex Mancastroppa, Matteo Matteu...