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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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Related topics

Related topics

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Bayesian interpretation of kernel regularizationCross-validation (statistics)Gaussian processGraph kernel

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Multi-Relational Learning at Scale with ADMM
Learning from multiple-relational data which contains noise, ambiguities, or duplicate entities is essential to a wide range of… 
2016
2016
Topic for a Master ’ s Thesis : An Analysis of Chaining in Multi-Target Prediction Intelligent Systems
  • 2016
  • Corpus ID: 4663542
The task of simultaneously predicting multiple target variables from a common set of input variables is known as multi-target… 
2014
2014
Full Bayesian multi-task learning for multi-output brain decoding and accommodating missing data
Multi-task learning (MTL) has recently been demonstrated to be highly promising for decoding multiple target variables from… 
2012
2012
Efficient multivariate modeling of cross border effects in European bond volatility spillover: A multiple objective artificial neural network approach
In this paper we extend prior efforts to engineer an efficient mapping of volatility transmission across various western- and… 
Review
2008
Review
2008
A Bayesian View of Challenges in Feature Selection : Multilevel Analysis , Feature Aggregation , Multiple Targets , Redundancy and Interaction
In the paper we discuss applications of the Bayesian approach to new challenges in relevance analysis. Earlier, we formulated a… 
Review
2008
Review
2008
A Bayesian View of Challenges in Feature Selection: Feature Aggregation, Multiple Targets, Redundancy and Interaction
Earlier, we formulated a Bayesian approach to Feature Subset Selection using Bayesian networks, which jointly estimate the… 
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