2. The method of claim 1 further comprising: classifying test patterns based at least in part on the set of feature vectors.
1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters.