PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A second order cone programming formulation for classifying missing data
Chiranjib Bhattacharyya, K.S. Pannagadatta and Alex Smola
In: NIPS 2004, December 2004, Vancouver.

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 particu- lar, we derive a robust formulation when the distribution is given by a normal distribution. It leads to Second Order Cone Programming formu- lation. Our method is applied to the problem of missing data, where it outperforms direct imputation.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2042
Deposited By:Alex Smola
Deposited On:16 January 2006