Patent ID: 11868862
Assignee: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method of modelling data, comprising:
training an objective function of a linear classifier using semisupervised learning based on a set of at least partially labelled noised semantic data, to derive a set of classifier weights corresponding to a plurality of dimensions;
approximating a marginalized loss function, based on a posterior probability distribution on the set of classifier weights of the linear classifier; and
implementing a compact classifier dependent on the marginalized loss function, for reconstructing an input with respect to the marginalized loss function, wherein the reconstructed input has a different accuracy of reconstruction selectively dependent on a respective dimension,
wherein the accuracy of reconstruction for a respective dimension is selectively dependent on a sensitivity of the linear classifier to differences in the input with respect to that respective dimension.