Skip to search formSkip to main contentSkip to account menu

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… 
Wikipedia

Related topics

Related topics

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

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2018
Review
2018
Multi-target prediction: a unifying view on problems and methods
Many problem settings in machine learning are concerned with the simultaneous prediction of multiple target variables of diverse… 
Highly Cited
2016
Highly Cited
2016
Multi-target regression via input space expansion: treating targets as inputs
In many practical applications of supervised learning the task involves the prediction of multiple target variables from a common… 
2015
2015
Multi-target regression from high-speed data streams with adaptive model rules
  • 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… 
2013
2013
Habitat modeling with single- and multi-target trees and ensembles
Highly Cited
2012
Highly Cited
2012
Multi-Label Classification Methods for Multi-Target Regression
Real world prediction problems often involve the simultaneous prediction of multiple target variables using the same set of… 
Highly Cited
2011
Highly Cited
2011
Multi-label Problem Transformation Methods: a Case Study
Traditional classication algorithms consider learning problems that contain only one label, i.e., each example is associated with… 
2010
2010
The Emotional Machine: A Machine Learning Approach to Online Prediction of User's Emotion and Intensity
This paper explores the feasibility of equipping computers with the ability to predict, in a context of a human computer… 
2008
2008
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees
We consider learning tasks where multiple target variables need to be predicted. Two approaches have been used in this setting… 
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… 
Highly Cited
2002
Highly Cited
2002
Ranking with Predictive Clustering Trees
A novel class of applications of predictive clustering trees is addressed, namely ranking. Predictive clustering trees, as… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License