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» AUC Optimization vs. Error Rate Minimization
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ICASSP
2011
IEEE
13 years 21 days ago
Proportionate-type normalized least mean square algorithm with gain allocation motivated by minimization of mean-square-weight d
In previous work, a water-filling algorithm was proposed which sought to minimize the mean square error (MSE) at any given time by optimally choosing the gains (i.e. step-sizes) ...
Kevin T. Wagner, Milos Doroslovacki
ICASSP
2010
IEEE
13 years 9 months ago
Noise-to-mask ratio minimization by weighted non-negative matrix factorization
This paper proposes a novel algorithm for minimizing the perceptual distortion in non-negative matrix factorization (NMF) based audio representation. We formulate the noise-to-mas...
Joonas Nikunen, Tuomas Virtanen
ICASSP
2011
IEEE
13 years 21 days ago
Speaker recognition using multiple kernel learning based on conditional entropy minimization
We applied a multiple kernel learning (MKL) method based on information-theoretic optimization to speaker recognition. Most of the kernel methods applied to speaker recognition sy...
Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru...
CORR
2007
Springer
104views Education» more  CORR 2007»
13 years 9 months ago
Searching for low weight pseudo-codewords
— Belief Propagation (BP) and Linear Programming (LP) decodings of Low Density Parity Check (LDPC) codes are discussed. We summarize results of instanton/pseudo-codeword approach...
Michael Chertkov, Mikhail G. Stepanov
CORR
2011
Springer
193views Education» more  CORR 2011»
13 years 22 days ago
The Rate of Convergence of AdaBoost
The AdaBoost algorithm was designed to combine many “weak” hypotheses that perform slightly better than random guessing into a “strong” hypothesis that has very low error....
Indraneel Mukherjee, Cynthia Rudin, Robert E. Scha...