Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Abstract. We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on phy...
Abstract. Phylogeny reconstruction from molecular data poses complex optimization problems: almost all optimization models are NP-hard and thus computationally intractable. Yet app...
Fault Abstraction and Collapsing Framework for Asynchronous Circuits Philip P. Shirvani, Subhasish Mitra Center for Reliable Computing Stanford University Stanford, CA Jo C. Eberge...
Philip P. Shirvani, Subhasish Mitra, Jo C. Ebergen...
We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...