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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://subscription.packtpub.com/book/big_data_and_business_intelligence/9781789957211/2/ch02lvl1sec17/transductive-support-vector-machines-tsvm
Transductive Support Vector Machines (TSVM) Another approach to the same problem is offered by the TSVM, proposed by T. Joachims (in Transductive Inference for Text Classification using Support Vector Machines, Joachims T., ICML Vol. 99/1999).
https://mitpress.universitypressscholarship.com/view/10.7551/mitpress/9780262033589.001.0001/upso-9780262033589-chapter-6
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 information for learning, in particular for the problem of text classification.
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.sciencedirect.com/science/article/pii/S0167865503000084
Transductive support vector machine is a well-known algorithm that realizes transductive learning in the field of support vector classification (Joachims, 1999a). This paper tries to find a more practical transductive inference solution for support vector classification applications.Cited by: 190
https://ieeexplore.ieee.org/document/4633779/
Abstract: Support vector machines have been extensively used in machine learning because of its efficiency and its theoretical background. This paper focuses on nu-transductive support vector machines for classification (nu-TSVC) and construct a new algorithm - Unconstrained nu-Transductive Support Vector Machines (Unu-TSVM).
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.
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