The Support Vector Machine Under Test Neurocomputing

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The support vector machine under test - ScienceDirect

    https://www.sciencedirect.com/science/article/pii/S0925231203004314
    Support vector machines yielded good performance, but were not top ranked on all data sets. For classification, simple statistical procedures and ensemble methods proved very competitive, mostly producing good results “out of the box” without the inconvenience of delicate and computationally expensive hyperparameter tuning.Cited by: 750

The support vector machine under test - ScienceDirect

    https://www.sciencedirect.com/science/article/abs/pii/S0925231203004314
    David Meyer was born in Vienna, Austria in 1973. He received a diploma of applied computer science from the Vienna University in 1998. After a 2-years period of business consulting, he joined the department of statistics and probability theory of the Vienna University of Technology as a research assistant, participating at the center of excellence: “Adaptive Information Systems and Modeling ...Cited by: 750

Neurocomputing Support Vector Machines ScienceDirect.com

    https://www.sciencedirect.com/journal/neurocomputing/vol/55/issue/1
    Support vector machine models in drug design: applications to drug transport processes and QSAR using simplex optimisations and variable selection Ulf Norinder Pages 337-346

Support vector machines under adversarial label ...

    https://dl.acm.org/doi/10.5555/2779626.2779777
    Home Browse by Title Periodicals Neurocomputing Vol. 160, No. C Support vector machines under adversarial label contamination research-article Support vector machines under …

When size matters: selection of training sets for support ...

    https://www.future-processing.pl/blog/when-size-matters-selection-of-training-sets-for-support-vector-machines/
    Support vector machine (SVM) is a supervised classifier which has been applied for solving a wide range of pattern recognition problems. However, training of SVMs may easily become their bottleneck, because of its time and memory requirements (O(t 3 ) and O(t 2 ), respectively, where t denotes the cardinality of the training set).

A new support vector machine with an optimal additive ...

    https://www.sciencedirect.com/science/article/pii/S0925231218312207
    1. Introduction. A kernel support vector machine (SVM) is one of the most popular classifiers, and it has been applied to a variety of fields due to its excellent classification performance , , , , , , , .Typical examples of nonlinear kernels include the polynomial kernel, the radial basis function (RBF) kernel and the Gaussian kernel, which definitely outperform linear SVM.Author: Jeonghyun Baek, Euntai Kim

Support vector machines under adversarial label contamination

    https://www.sciencedirect.com/science/article/pii/S0925231215001198
    The algorithm starts by assessing how each singleton flip impacts V L and proceeds by randomly sampling a set of P initial singleton flips to serve as initial clusters. For each of these clusters, k, we select a random set of mutations to it (i.e., a mutation is a change to a single flip in the cluster), which we then evaluate (using the empirical 0–1 loss) to form a matrix Δ.Cited by: 88

Support-vector machine - Wikipedia

    https://en.wikipedia.org/wiki/Support-vector_machine
    The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) algorithm for the hinge loss. Seen this way, support vector machines belong to a natural class of algorithms for statistical inference, and many of its unique features are due to the behavior of the hinge loss.

Support Vector Machines under Adversarial Label …

    http://pralab.diee.unica.it/sites/default/files/biggio14-neurocomp.pdf
    Support Vector Machines under Adversarial Label Contamination Huang Xiaoa, Battista Biggiob,, Blaine Nelsonb, Han Xiao a, Claudia Eckert , Fabio Rolib aDepartment of Computer Science, Technical University of Munich, Boltzmannstr. 3, 85748, Garching, Germany bDepartment of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi, 09123, Cagliari, Italy

Support vector machine : Wikis (The Full Wiki)

    http://www.thefullwiki.org/Support_vector_machine
    Classifying data is a common task in machine learning.Suppose some given data points each belong to one of two classes, and the goal is to decide which class a new data point will be in. In the case of support vector machines, a data point is viewed as a p-dimensional vector (a list of p numbers), and we want to know whether we can separate such points with a p − 1-dimensional hyperplane.



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