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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://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 …
http://www.cs.cmu.edu/~guestrin/Class/10701-S06/Slides/tsvms-pca.pdf
Transductive SVMs Machine Learning – 10701/15781 Carlos Guestrin Carnegie Mellon University April 17 th, 2006 Reading: Vapnik 1998 Joachims 1999 (see class website) 2 Semi-supervised learning and discriminative models ... Transductive support vector machines (TSVMs) w. x + b = + 1 w. x
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://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.cs.cornell.edu/people/tj/svm_light/
Training algorithm for transductive Support Vector Machines. Integrated core QP-solver based on the method of Hildreth and D'Espo. Uses folding in the linear case, which speeds up linear SVM training by an order of magnitude. Allows linear cost models. Faster in general. V2.00 - V2.01. Improved interface to PR_LOQO Source code for SVM light V2.01
https://calculatedcontent.com/2014/09/23/machine-learning-with-missing-labels-transductive-svms/
Sep 23, 2014 · Machine Learning with Missing Labels: Transductive SVMs. September 23, 2014 Charles H Martin, PhD Uncategorized 15 comments. SVMs are great for building text classifiers–if you have a set of very high quality, labeled documents. ... W. Pan On Transductive Support Vector Machines …
https://www.cs.cornell.edu/people/tj/svm_light/old/svm_light_v4.00.html
There is also another regression support vector machine based on SVM light available at the AI-Unit: mySVM. Description. SVM light is an implementation of Vapnik's Support Vector Machine [Vapnik, 1995] for the problem of pattern recognition and for the problem of regression.
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