A Simple Randomized Quantization Algorithm for Neural Network

This paper explores some algorithms for automatic quantization of real-valued datasets using thermometer codes for pattern classiication applications. Experimental results indicate that a relatively simple randomized thermometer code generation technique can result in quantized datasets that when used to train simple perceptrons, can yield generalization on test data that is substantially better than that obtained with their unquantized counterparts.