Vanishing component analysis

Roi Livni, David Lehavi, Sagi Schein, Hila Nachlieli, Shai Shalev-Shwartz, Amir Globerson

Research output: Contribution to conferencePaperpeer-review

28 Scopus citations


The vanishing ideal of a set of points, S ⊂ ℝn, is the set of all polynomials that attain the value of zero on all the points in S. Such ideals can be compactly represented using a small set of polynomials known as generators of the ideal. Here we describe and analyze an efficient procedure that constructs a set of generators of a vanishing ideal. Our procedure is numerically stable, and can be used to find approximately vanishing polynomials. The resulting polynomials capture nonlinear structure in data, and can for example be used within supervised learning. Empirical comparison with kernel methods show that our method constructs more compact classifiers with comparable accuracy.

Original languageAmerican English
Number of pages9
StatePublished - 2013
Event30th International Conference on Machine Learning, ICML 2013 - Atlanta, GA, United States
Duration: 16 Jun 201321 Jun 2013


Conference30th International Conference on Machine Learning, ICML 2013
Country/TerritoryUnited States
CityAtlanta, GA


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