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Kernel methods for vector output

Kernel methods are a well-established tool to analyze the relationship between input data and the corresponding output of a function. Kernels… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2018
Review
2018
Many problem settings in machine learning are concerned with the simultaneous prediction of multiple target variables of diverse… 
Highly Cited
2016
Highly Cited
2016
In many practical applications of supervised learning the task involves the prediction of multiple target variables from a common… 
2015
2015
  • J. Duarte, João Gama
  • IEEE International Conference on Data Science and…
  • 2015
  • Corpus ID: 18262582
Many real life prediction problems involve predicting a structured output. Multi-target regression is an instance of structured… 
Highly Cited
2012
Highly Cited
2012
Real world prediction problems often involve the simultaneous prediction of multiple target variables using the same set of… 
Highly Cited
2011
Highly Cited
2011
Traditional classication algorithms consider learning problems that contain only one label, i.e., each example is associated with… 
2010
2010
This paper explores the feasibility of equipping computers with the ability to predict, in a context of a human computer… 
2008
2008
We consider learning tasks where multiple target variables need to be predicted. Two approaches have been used in this setting… 
Review
2008
Review
2008
In the paper we discuss applications of the Bayesian approach to new challenges in relevance analysis. Earlier, we formulated a… 
Highly Cited
2002
Highly Cited
2002
A novel class of applications of predictive clustering trees is addressed, namely ranking. Predictive clustering trees, as…