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IJPRAI
2010
151views more  IJPRAI 2010»
15 years 4 months ago
Structure-Embedded AUC-SVM
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...
Yunyun Wang, Songcan Chen, Hui Xue
SAC
2006
ACM
16 years 11 days ago
Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data
Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Hwanjo Yu, Xiaoqian Jiang, Jaideep Vaidya
ICML
2007
IEEE
16 years 7 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...
PR
2007
165views more  PR 2007»
15 years 6 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
TIFS
2008
194views more  TIFS 2008»
15 years 6 months ago
Detection of Double-Compression in JPEG Images for Applications in Steganography
This paper presents a method for detection of double JPEG compression and a maximum likelihood estimator of the primary quality factor. These methods are essential for construction...
Tomás Pevný, Jessica J. Fridrich