We introduce a novel methodology for calculating discriminative codes for different classes of vectors with respect to the same dictionary. This is accomplished by introducing and quantifying the concept of ‘mutual exclusivity’ between two classes of vectors (endowed possibly with different probabilistic structures) in a manner amenable to convex programming. We study theoretical properties of our mutual exclusivity operator and experimentally demonstrate its capability in generating effective discriminative codes that successfully incorporate both intra-class and inter-class characteristics. We conclude with a brief discussion of a generalization our mutual exclusivity operator to handle arbitrary number of classes, together with future directions emanating from this work.
['Raghu G. Raj']
An asymptotically convex approach to discriminative coding