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Transduction (machine learning)

Known as: Transductive learning, Transductive inference, Transductive logic 
In logic, statistical inference, and supervised learning,transduction or transductive inference is reasoning fromobserved, specific (training) cases… 
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Papers overview

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Highly Cited
2017
Highly Cited
2017
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder… 
Highly Cited
2012
Highly Cited
2012
Many machine learning tasks can be expressed as the transformation---or \emph{transduction}---of input sequences into output… 
Highly Cited
2010
Highly Cited
2010
• Supervised learning --where the algorithm generates a function that maps inputs to desired outputs. One standard formulation of… 
Review
2009
Review
2009
Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs… 
Highly Cited
2003
Highly Cited
2003
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or… 
Review
2002
Review
2002
In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and… 
Highly Cited
1999
Highly Cited
1999
Introduction to support vector learning roadmap. Part 1 Theory: three remarks on the support vector method of function estimation… 
Highly Cited
1998
Highly Cited
1998
We describe a method for predicting a classification of an object given classifications of the objects in the training set… 
Highly Cited
1998
Highly Cited
1998
We introduce a semi-supervised support vector machine (S3VM) method. Given a training set of labeled data and a working set of…