A Second Order Cone programming Formulation for Classifying Missing Data

A Second Order Cone programming Formulation for Classifying Missing Data. Bhattacharyya, C., Shivaswamy, P. K, & Smola, A. J
abstract bibtex

We propose a convex optimization based strategy to deal with uncertainty in the observations of a classiﬁcation problem. We assume that instead of a sample (xi, yi) a distribution over (xi, yi) is speciﬁed. In particular, we derive a robust formulation when the distribution is given by a normal distribution. It leads to Second Order Cone Programming formulation. Our method is applied to the problem of missing data, where it outperforms direct imputation.

@article{bhattacharyya_second_nodate,
	title = {A {Second} {Order} {Cone} programming {Formulation} for {Classifying} {Missing} {Data}},
	abstract = {We propose a convex optimization based strategy to deal with uncertainty in the observations of a classiﬁcation problem. We assume that instead of a sample (xi, yi) a distribution over (xi, yi) is speciﬁed. In particular, we derive a robust formulation when the distribution is given by a normal distribution. It leads to Second Order Cone Programming formulation. Our method is applied to the problem of missing data, where it outperforms direct imputation.},
	language = {en},
	author = {Bhattacharyya, Chiranjib and Shivaswamy, Pannagadatta K and Smola, Alex J},
	keywords = {⛔ No DOI found},
	pages = {8},
}

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