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» An Algorithm for Iterative Selection of Blocks of Features
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ICML
1994
IEEE
13 years 10 months ago
Efficient Algorithms for Minimizing Cross Validation Error
Model selection is important in many areas of supervised learning. Given a dataset and a set of models for predicting with that dataset, we must choose the model which is expected...
Andrew W. Moore, Mary S. Lee
TASLP
2011
13 years 1 months ago
Time-Frequency Cepstral Features and Heteroscedastic Linear Discriminant Analysis for Language Recognition
Abstract—The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, S...
Weiqiang Zhang, Liang He, Yan Deng, Jia Liu, M. T....
ICPR
2004
IEEE
14 years 7 months ago
Efficient Calculation of the Complete Optimal Classification Set
Feature and structure selection is an important part of many classification problems. In previous papers, an approach called basis pursuit classification has been proposed which p...
Martin Brown, Nicholas Costen, Shigeru Akamatsu
ICCAD
2001
IEEE
101views Hardware» more  ICCAD 2001»
14 years 3 months ago
Instruction Generation for Hybrid Reconfigurable Systems
In this work, we present an algorithm for simultaneous template generation and matching. The algorithm profiles the graph and iteratively contracts edges to create the templates. ...
Ryan Kastner, Seda Ogrenci Memik, Elaheh Bozorgzad...
TCOM
2010
111views more  TCOM 2010»
13 years 5 months ago
Design of irregular LDPC codes with optimized performance-complexity tradeoff
—The optimal performance-complexity tradeoff for error-correcting codes at rates strictly below the Shannon limit is a central question in coding theory. This paper proposes a nu...
Benjamin Smith, Masoud Ardakani, Wei Yu, Frank R. ...