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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
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 …
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
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...
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.
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.
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
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
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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