We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
We propose a new methodology to look at the fitness contributions (semantics) of different schemata in Genetic Programming (GP). We hypothesize that the significance of a schem...
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
With stock surpluses and shortages representing one of the greatest elements of risk to wholesalers, a solution to the multiretailer supply chain management problem would result i...
Caio Soares, Gerry V. Dozier, Emmett Lodree, Jared...
In this paper the effectiveness of a corrective learning algorithm MIL (Mirror Image Learning) [1], [2] is comparatively studied with that of GLVQ (Generalized Learning Vector Qua...