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Face pose discrimination using support vector machines (SVM)
Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002This paper describes an approach for the problem of face pose discrimination using support vector machines (SVM). Face pose discrimination means that one can label the face image as one of several known poses. Face images are drawn from the standard FERET database. The training set consists of 150 images equally distributed among frontal, approximately
J. Huang, X. Shao, H. Wechsler
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2009
Support vector machines (SVMs), including support vector classifier (SVC) and support vector regressor (SVR), are among the most robust and accurate methods in all well-known data mining algorithms. SVMs, which were originally developed by Vapnik in the 1990s [1-11], have a sound theoretical foundation rooted in statistical learning theory, require only
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Support vector machines (SVMs), including support vector classifier (SVC) and support vector regressor (SVR), are among the most robust and accurate methods in all well-known data mining algorithms. SVMs, which were originally developed by Vapnik in the 1990s [1-11], have a sound theoretical foundation rooted in statistical learning theory, require only
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RD-SVM: A resilient distributed support vector machine
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016Support vector machines (SVMs) are one of the most widely used supervised learning algorithms for classification problems. Recent years have witnessed an increasing interest in distributed variants of SVMs, in which the (labeled) training data is distributed across different nodes.
Zhixiong Yang, Waheed U. Bajwa
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Gases identification with Support Vector Machines technique (SVMs)
2014 1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), 2014Air pollution is an olfactory pollution because many polluting gases have a strong odor even at low concentrations. These pollutants are natural or anthropogenic emission sources. This pollution has many harmful effects on human health or upon the environment. So it is necessary to detect the pollution to reduce its effects.
Souhir Bedoui +3 more
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Fault types classification using support vector machine (SVM)
AIP Conference Proceedings, 2019Fault type classification is an important task in order to provide reliable electrical service to the customer. In this work, Support Vector Machine (SVM) is used for fault classification in distribution systems. This work proposes an effective fault type classifying method using Support Vector Machine to identify various fault type. Classification and
Lilik J. Awalin +2 more
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Asymptotic efficiency of kernel support vector machines (SVM)
Cybernetics and Systems Analysis, 2009The paper analyzes the asymptotic properties of Vapnik's SVM-estimates of a regression function as the size of the training sample tends to infinity. The estimation problem is considered as infinite-dimensional minimization of a regularized empirical risk functional in a reproducing kernel Hilbert space.
V. I. Norkin, M. A. Keyzer
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Sequential bootstrapped support vector machines a SVM accelerator
Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2006Support vector machine has obtained much success in machine learning. But it requires to solve a quadratic optimization (QP) problem so that its training time increases dramatically with the increase of training set. Hence, standard SVM with batch learning has difficulty in handling large scale problems.
null Xuchun Li, null Yan Zhu, E. Sung
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Sparse Optimization in Adversarial Support Vector Machine (SVM)
2021Supervised classification models, such as SVM, aim at predicting the class membership of the incoming samples. Malicious inputs are designed to cheat a vulnerable classifier, leading to a wrong prediction. We focus our analysis on the search of the smallest perturbations of samples producing a failure of the classification process.
Enrico Gorgone +4 more
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