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