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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
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://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.researchgate.net/publication/250884384_On_Transductive_Support_Vector_Machines
Transductive support vector machines (TSVM) has been widely used as a means of treating partially labeled data in semi- supervised learning. Around it, there has been mystery because of …
https://www.sciencedirect.com/science/article/pii/S0925231217300292
In this paper, we propose a robust and fast transductive support vector machine (RTSVM) classifier that can be applied to large-scale data. To this end, we use the robust Ramp loss instead of Hinge loss for labeled data samples.Cited by: 6
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 an additional source of information about margins.Cited by: 188
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). The idea is to keep the original objective with two sets of slack variables: the first for the labeled ...
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 [9] ...
https://www.semanticscholar.org/paper/Transductive-Inference-for-Text-Classification-Joachims/74b1a9e50f18af8a7b9f8dd38f40e0466ad7a8e8
This paper introduces Transductive Support Vector Machines (TSVMs) for text classi cation. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try to minimize misclassi cations of just those particular examples.
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