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 17:
18. A computer readable medium containing non-transitory instructions for controlling at least one programmable automated processor to perform a method, comprising:
instructions for receiving a semantic input;
instructions for automatically classifying the semantic input according to a plurality of dimensions each associated with a respective class label with a compact classifier comprising instructions for implementing a marginalized loss function; and
instructions for communicating a set of associated class labels for the semantic input;
wherein:
the marginalized loss function is based on a posterior probability distribution on a set of classifier weights of a linear classifier corresponding to the plurality of dimensions for reconstructing a semantic input;
the linear classifier is trained based on an objective function using semisupervised learning using on a set of at least partially labelled noised semantic data; and
the reconstructed semantic input has a different accuracy of reconstruction selectively dependent on a respective class label,
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.