⌘+K

Pulse Explore Communities Researchers Journals

Home Communities Explore

March 1, 2003Journal of Machine Learning Research

Use of the zero norm with linear models and kernel methods

WestonJason ElisseeffAndré SchölkopfBernhard TippingMike

View at Publisher

Ask AI

Bookmark

Share

Abstract

We explore the use of the so-called zero-norm of the parameters of linear models in learning. Minimization of such a quantity has many uses in a machine learning context: for variable or feature se...

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

WestonJason et al. (2003) studied this question.

synapsesocial.com/papers/6a82c2bfe0918b5470d11c8d https://doi.org/10.5555/944919.944982

View at Publisher

Ask AI

Bookmark

Share

Keep reading

Synapse has enriched 5 related papers. Consider them for comparative context:

1Adaptive Online Prediction by Following the Perturbed Leader.Journal of Machine Learning Research · Thu,
2MEKA: A multi-label/multi-target extension to WekaJournal of Machine Learning Research · Fri,
3River: Machine learning for streaming data in pythonJournal of Machine Learning Research · Tue,
4An Introduction to Artificial Prediction Markets for ClassificationJournal of Machine Learning Research · Mon,
5Pattern Recognition for Conditionally Independent DataJournal of Machine Learning Research · Thu,

More from Journal of Machine Learning Research

Marginal Likelihood Integrals for Mixtures of Independence ModelsWed,
Undercomplete Blind Subspace DeconvolutionWed,
Nonlinear Models Using Dirichlet Process MixturesWed,
Matrix Completion from Noisy EntriesTue,
Manifold Learning: The Price of NormalizationTue,