We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
We present a constraint-based algorithm for the synthesis of invariants expressed in the combined theory of linear arithmetic and uninterpreted function symbols. Given a set of pro...
Dirk Beyer, Thomas A. Henzinger, Rupak Majumdar, A...
Mixin modules are proposed as an extension of a class-based programming language. Mixin modules combine parallel extension of classes, including extension of the self types for th...
—Owing to the absence of any static support structure, Ad-hoc networks are prone to link failures. The ‘shortest path seeking’ routing protocols may not lead to stable routes...
Sulabh Agarwal, Ashish Ahuja, Jatinder Pal Singh, ...
We introduce calling context graphs and various static and theorem proving based analyses that together provide a powerful method for proving termination of programs written in fea...