Globally Optimal Design of a Distributed Scalar Quantizer for Linear Classification

This work is concerned with the design of a distributed scalar quantizer (DSQ) with two encoders, for linear classification. The objective of the optimization is to minimize the classification error of the classifier applied to the quantized inputs in the training sequence with respect to the classifier applied on unquantized inputs. We prove that the optimal DSQ design problem is equivalent to a minimum weight path problem with some …