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» Optimal convex error estimators for classification
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ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...
TSP
2010
13 years 2 months ago
Joint nonlinear channel equalization and soft LDPC decoding with Gaussian processes
In this paper, we introduce a new approach for nonlinear equalization based on Gaussian processes for classification (GPC). We propose to measure the performance of this equalizer ...
Pablo M. Olmos, Juan José Murillo-Fuentes, ...
ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun
SIAMJO
2011
13 years 2 months ago
Erratum: Validated Linear Relaxations and Preprocessing: Some Experiments
This is a correction to R. B. Kearfott and S. Hongthong’s article [SIAM J. Optim., 16 (2005), pp. 418–433]. DOI. 10.1137/100816080 There are errors in column 4 (entitled “Und...
R. Baker Kearfott