New Support Vector Algorithms Bibtex

Searching for New Support Vector Algorithms Bibtex information? Find all needed info by using official links provided below.


New Support Vector Algorithms - Purdue University

    http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
    New Support Vector Algorithms ... We propose a new class of support vector algorithms for regression and classi” cation. In these algorithms, a parameterºlets one effectively con-trol the number of support vectors. While this can be useful in its own right, the parameterization has the additional bene” t of enabling us to

CiteSeerX — New Support Vector Algorithms

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.6040
    BibTeX @MISC{Schölkopf00newsupport, author = {Bernhard Schölkopf and Alex J. Smola and Robert C. Williamson and Peter L. Bartlett}, title = {New Support Vector Algorithms}, year = …

CiteSeerX — New Support Vector Algorithms

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.94.2928
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter º lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of …

New Support Vector Algorithms Neural Computation

    https://dl.acm.org/citation.cfm?id=1139691
    We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the …Cited by: 3132

Learning with Kernels: Support Vector Machines ...

    https://direct.mit.edu/books/book/1821/Learning-with-KernelsSupport-Vector-Machines
    In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept …

New Support Vector Algorithms - Alex Smola

    http://alex.smola.org/papers/2000/SchSmoWilBar00.pdf
    New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracy "is specified a priori. It is then attempted to fit a tube with radius "to the data. The trade-off between model complexity and points lying outside the tube (with positive slack variables »)is determined by minimizing the expression 1.5.

New Support Vector Algorithms — Kernel Machines

    http://www.kernel-machines.org/publications/SchSmoWilBar98/bibliography_exportForm
    New Support Vector Algorithms. Books. Software. Annual Workshop. JMLR. Links. Tutorials. News ... A specific renderer to export bibliographical references in BiBTeX format. Note: If the output encoding of the BiBTeX renderer is not unicode capable, all non-ASCII characters will be resolved to LaTeX entities.

Shrinking the Tube: A New Support Vector Regression Algorithm

    https://www.researchgate.net/publication/2611423_Shrinking_the_Tube_A_New_Support_Vector_Regression_Algorithm
    A new algorithm for Support Vector regression is described. For a priori chosen , it automatically adjusts a flexible tube of minimal radius to the data such that at most a fraction of the data ...

New support vector algorithms with parametric insensitive ...

    https://dl.acm.org/citation.cfm?id=1660541
    In this paper, a modification of v-support vector machines (v-SVM) for regression and classification is described, and the use of a parametric insensitive/margin model with an arbitrary shape is demonstrated. This can be useful in many cases, especially when the noise is heteroscedastic, that is, the noise strongly depends on the input value x.Cited by: 100

(PDF) A New Support Vector Finder Method, Based on ...

    https://www.researchgate.net/publication/319765351_A_New_Support_Vector_Finder_Method_Based_on_Triangular_Calculations_and_K-means_Clustering
    In this paper, a new support vector finder method, based on triangle, has been presented, which finds support vectors based on triangular calculations, like calculating triangle angles, area and ...

New Support Vector Algorithms - Purdue University

    http://www.stat.purdue.edu/~yuzhu/stat598m3/Papers/NewSVM.pdf
    New Support Vector Algorithms 1209 Figure 1: In SV regression, a desired accuracyeis speci” ed a priori.It is then attempted to ” t a tube with radiuseto the data.The trade-off between model

CiteSeerX — New Support Vector Algorithms

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.94.2928
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter º lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other ...

CiteSeerX — New Support Vector Algorithms

    http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.41.4373
    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We describe a new class of Support Vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of Support Vectors. While this can be useful in its own right, the parametrization has the additional benefit of enabling us to eliminate one of the other ...

New Support Vector Algorithms Neural Computation

    https://dl.acm.org/citation.cfm?id=1139691
    We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of support vectors. While this can be...Cited by: 3132

Learning with Kernels: Support Vector Machines ...

    https://direct.mit.edu/books/book/1821/Learning-with-KernelsSupport-Vector-Machines
    In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks.

Shrinking the Tube: A New Support Vector Regression Algorithm

    https://www.researchgate.net/publication/2611423_Shrinking_the_Tube_A_New_Support_Vector_Regression_Algorithm
    A new algorithm for Support Vector regression is described. For a priori chosen , it automatically adjusts a flexible tube of minimal radius to the data such that at most a fraction of the data ...

New support vector algorithms with parametric insensitive ...

    https://dl.acm.org/citation.cfm?id=1660541
    In this paper, a modification of v-support vector machines (v-SVM) for regression and classification is described, and the use of a parametric insensitive/margin model with an arbitrary shape is demonstrated. This can be useful in many cases, especially when the noise is heteroscedastic, that is, the noise strongly depends on the input value x.Cited by: 100

New Support Vector Algorithms — Kernel Machines

    http://www.kernel-machines.org/publications/SchSmoWilBar98/bibliography_exportForm
    New Support Vector Algorithms. Books. Software. Annual Workshop. JMLR. Links. Tutorials. News ... A specific renderer to export bibliographical references in BiBTeX format. Note: If the output encoding of the BiBTeX renderer is not unicode capable, all non-ASCII characters will be resolved to LaTeX entities.

New support vector algorithms with parametric insensitive ...

    https://www.sciencedirect.com/science/article/pii/S0893608009002019
    Like the previous v-SVM, the proposed new support vector algorithms with parametric insensitive/margin model have the advantage of using the parameter 0 ≤ v …Cited by: 100

(PDF) A New Support Vector Finder Method, Based on ...

    https://www.researchgate.net/publication/319765351_A_New_Support_Vector_Finder_Method_Based_on_Triangular_Calculations_and_K-means_Clustering
    In this paper, a new support vector finder method, based on triangle, has been presented, which finds support vectors based on triangular calculations, like calculating triangle angles, area and ...

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.

SVM-Light: Support Vector Machine - Cornell University

    https://www.cs.cornell.edu/people/tj/svm_light/index.html
    SVM light is an implementation of Vapnik's Support Vector Machine [Vapnik, 1995] for the problem of pattern recognition, for the problem of regression, and for the problem of learning a ranking function. The optimization algorithms used in SVM light are described in [Joachims, 2002a]. [Joachims, 1999a]. The algorithm has scalable memory ...

A New Support Vector Machine and Artificial Neural ...

    https://asmedigitalcollection.asme.org/energyresources/article/136/2/024502/373129/A-New-Support-Vector-Machine-and-Artificial-Neural
    Stuck pipe is known to be influenced by drilling fluid properties and other parameters, such as the characteristics of rock formations. In this paper, we develop a support-vector-machine (SVM) based model to predict stuck pipe during drilling design and operations. To develop the model, we use a dataset, including stuck and nonstuck cases.

New Unsupervised Support Vector Machines SpringerLink

    https://link.springer.com/chapter/10.1007%2F978-3-642-02298-2_89
    Support Vector Machines (SVMs) have been dominant learning techniques for more than ten years, and mostly applied to supervised learning problems. Recently nice results are obtained by two-class unsupervised classification algorithms where the optimization problems based on Bounded C -SVMs, Bounded ν -SVMs and Lagrangian SVMs respectively are ...

Spectral Algorithms for Computing Fair Support Vector Machines

    https://arxiv.org/abs/1710.05895
    Classifiers and rating scores are prone to implicitly codifying biases, which may be present in the training data, against protected classes (i.e., age, gender, or race). So it is important to understand how to design classifiers and scores that prevent discrimination in predictions. This paper develops computationally tractable algorithms for designing accurate but fair support vector ...

New support vector algorithms for multicategorical data ...

    https://infoscience.epfl.ch/record/33301
    Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithms to learn from visual data is a difficult task. More than fifty years ago, Rosenblatt proposed the perceptron algorithm. The perceptron ...

Optimization of support vector machine based multi-fault ...

    https://journals.sagepub.com/doi/abs/10.1177/0954406213477777
    In the present work, a multi-fault classification of gears has been attempted by the support vector machine learning technique using the vibration data in time domain. A proper utilization of the support vector machine is based on the selection of support vector machine parameters.

Support Vector Machine with Graphical Network Structures ...

    https://easychair.org/publications/preprint/g6d1
    The implementation of the proposed learning algorithms is computationally easy and fast. We apply the new algorithms to analyze the data arising from a gene expression study. Keyphrases: Classification, graphical model, network structure, Support Vector Machine

Direct comparison between support vector machine and ...

    https://academic.oup.com/jamia/article/19/5/917/723897
    In 2011 Matwin et al published a letter to JAMIA entitled ‘Performance of SVM and Bayesian classifiers on the systematic review classification task’.1 This letter continued a discussion on the relative benefits of using support vector machine (SVM) and Bayesian techniques for performing systematic reviews.2–4 In particular, it was suggested that the running time of algorithms must be ...

Prediction of Apoptosis Protein Locations with Genetic ...

    http://www.eurekaselect.com/openurl/content.php?genre=article&issn=0929-8665&volume=17&issue=12&spage=1473
    Prediction of Apoptosis Protein Locations with Genetic Algorithms and Support Vector Machines Through a New Mode of Pseudo Amino Acid Composition. ... Prediction of Apoptosis Protein Locations with Genetic Algorithms and Support Vector Machines Through a New Mode of Pseudo Amino Acid Composition. ... BibTeX. Text. Content: Citation Only ...

Learning to Classify Text Using Support Vector Machines ...

    https://books.google.com/books/about/Learning_to_Classify_Text_Using_Support.html?id=GNTZjXHjB7kC
    Apr 30, 2002 · Learning To Classify Text Using Support Vector Machines gives a complete and detailed description of the SVM approach to learning text classifiers, including training algorithms, transductive text classification, efficient performance estimation, and a …4/5(1)

A new incremental learning algorithm based on Support ...

    https://www.spiedigitallibrary.org/conference-proceedings-of-spie/7496/1/A-new-incremental-learning-algorithm-based-on-Support-Vector-Machines/10.1117/12.832552.full
    30 October 2009 A new incremental learning algorithm based on Support Vector Machines. Zuying Miao; ... we first analyzed the possible change of support vector set after new samples are added, then presented a new support vector machine incremental learning algorithm. ... Efficient inference algorithms for hybrid dynamic Bayesian networks (HDBN ...

GitHub - AFAgarap/wisconsin-breast-cancer: [ICMLSC 2018 ...

    https://github.com/AFAgarap/wisconsin-breast-cancer/
    On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset. This paper was presented at the 2nd International Conference on Machine Learning and Soft Computing (ICMLSC) in Phu Quoc Island, Vietnam last February 2-4, 2018.

An Efficient Training Algorithm for Kernel Survival ...

    https://arxiv.org/abs/1611.07054
    Nov 21, 2016 · Survival analysis is a fundamental tool in medical research to identify predictors of adverse events and develop systems for clinical decision support. In order to leverage large amounts of patient data, efficient optimisation routines are paramount. We propose an efficient training algorithm for the kernel survival support vector machine (SSVM). We directly optimise the primal objective ...



How to find New Support Vector Algorithms Bibtex information?

Follow the instuctions below:

  • Choose an official link provided above.
  • Click on it.
  • Find company email address & contact them via email
  • Find company phone & make a call.
  • Find company address & visit their office.

Related Companies Support