Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
In this paper, we develop algorithms for robust linear regression by leveraging the connection between the problems of robust regression and sparse signal recovery. We explicitly ...
Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by microa...
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...