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» On the Complexity of Error Explanation
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LREC
2010
166views Education» more  LREC 2010»
15 years 7 months ago
Learning Based Java for Rapid Development of NLP Systems
Today's natural language processing systems are growing more complex with the need to incorporate a wider range of language resources and more sophisticated statistical metho...
Nick Rizzolo, Dan Roth
171
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HIS
2004
15 years 7 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
WSCG
2003
164views more  WSCG 2003»
15 years 7 months ago
Refinement and Hierarchical Coarsening Schemes for Triangulated Surfaces
We present a refinement and a coarsening (also simplification or decimation) algorithm for the adaptive representation of bivariate functions. The algorithms have proved to be eff...
José P. Suárez, Angel Plaza
ICASSP
2010
IEEE
15 years 6 months ago
On linear versus non-linear magnitude-DFT estimators and the influence of super-Gaussian speech priors
Although the linear mean-squared error (MSE) complex-DFT estimator, i.e., the Wiener filter, is well-known, its magnitude-DFT (MDFT) counterpart has never been considered in the ...
Richard C. Hendriks, Richard Heusdens
AUTOMATICA
2008
139views more  AUTOMATICA 2008»
15 years 6 months ago
Structured low-rank approximation and its applications
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equival...
Ivan Markovsky