For Transductive Support Vector

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Transductive SVMs

    http://www.cs.cmu.edu/~guestrin/Class/10701-S06/Slides/tsvms-pca.pdf
    Transductive support vector machines (TSVMs) w. x ... transductive SVMs What is transductive v. semi-supervised learning Formulation for transductive SVM can also be used for semi-supervised learning Optimization is hard! Integer program There are simple heuristic solution methods that

Transduction (machine learning) - Wikipedia

    https://en.wikipedia.org/wiki/Transduction_(machine_learning)
    An example of an algorithm in this category is the Transductive Support Vector Machine (TSVM). A third possible motivation which leads to transduction arises through the need to approximate. If exact inference is computationally prohibitive, one may at least try to make sure that …

On Transductive Support Vector Machines - Statistics

    http://users.stat.umn.edu/~xshen/paper/tsvm.pdf
    transductive support vector machine (TSVM; Vapnik, 1998), which remains mysterious, particularly its “al-leged” unstable performance in empirical studies. TSVM seeks the largest separation between labeled and unlabeled data through regularization. In em-pirical studies, it performs well in text classification

What are the Transductive Support Vector Machines (TSVMs ...

    https://www.quora.com/What-are-the-Transductive-Support-Vector-Machines-TSVMs
    The objective function for regular SVM maximizes the margin, alongwith the constraints that positive datapoints and negative datapoints are on opposite sides of the separating hyperplane. The regular SVM formulation can use only labeled datapoints...

Machine Learning with Missing Labels: Transductive SVMs

    https://calculatedcontent.com/2014/09/23/machine-learning-with-missing-labels-transductive-svms/
    Sep 23, 2014 · [7] Ran El-Yaniv, Dmitry Pechyony, Transductive Rademacher Complexity and its Applications [8] J. Wang, X. Shen, W. Pan On Transductive Support Vector Machines [9] C. Yu , Transductive Learning of Structural SVMs via Prior Knowledge Constraints [10] Fabian Gieseke, Antti Airola, Tapio Pahikkala, and Oliver Kramer.

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, ... Training algorithm for transductive Support Vector Machines. Integrated core QP-solver based on the method of Hildreth and D'Espo.

Learning with progressive transductive support vector machine

    https://www.sciencedirect.com/science/article/pii/S0167865503000084
    Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead of an inductive one in support vector classifiers, the working set can be used as …Cited by: 188

A Transductive Support Vector Machine Algorithm Based on ...

    https://www.sciencedirect.com/science/article/pii/S2212671612000601
    This article is a further study on transductive learning, trying to find a more common transductive learning algorithm than the existing methods. According to the inherent characteristics of support vector machine classification, this article design a transductive support vector machine algorithm based on spectral clustering (Shi and Malik, 2000).Cited by: 2

Transductive Support Vector Machines - MIT Press Scholarship

    https://mitpress.universitypressscholarship.com/view/10.7551/mitpress/9780262033589.001.0001/upso-9780262033589-chapter-6
    This chapter discusses the transductive learning setting proposed by Vapnik where predictions are made only at a fixed number of known test points. Transductive support vector machines (TSVMs) implement the idea of transductive learning by including test points in the computation of the margin. This chapter provides some examples for why the margin on the test examples can provide useful prior ...



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