The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 30, 2014

Filed:

Dec. 13, 2011
Applicants:

Cedric Archambeau, Grenoble, FR;

Shengbo Guo, Saint-Martin-d'Heres, FR;

Onno Zoeter, Grenoble, FR;

Jean-marc Andreoli, Meylan, FR;

Inventors:

Cedric Archambeau, Grenoble, FR;

Shengbo Guo, Saint-Martin-d'Heres, FR;

Onno Zoeter, Grenoble, FR;

Jean-Marc Andreoli, Meylan, FR;

Assignee:

Xerox Corporation, Norwalk, CT (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01); G06F 19/24 (2011.01);
U.S. Cl.
CPC ...
Abstract

Multi-task regression or classification includes optimizing parameters of a Bayesian model representing relationships between D features and P tasks, where D≧1 and P≧1, respective to training data comprising sets of values for the D features annotated with values for the P tasks. The Bayesian model includes a matrix-variate prior having features and tasks dimensions of dimensionality D and P respectively. The matrix-variate prior is partitioned into a plurality of blocks, and the optimizing of parameters of the Bayesian model includes inferring prior distributions for the blocks of the matrix-variate prior that induce sparseness of the plurality of blocks. Values of the P tasks are predicted for a set of input values for the D features using the optimized Bayesian model. The optimizing also includes decomposing the matrix-variate prior into a product of matrices including a matrix of reduced rank in the tasks dimension that encodes correlations between tasks.


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