Abstract. Combining classical approximability questions with parameterized complexity, we introduce a theory of parameterized approximability. The main intention of this theory is ...
Experimental data show that biological synapses behave quite differently from the symbolic synapses in all common artificialneuralnetwork models. Biological synapses are dynamic, ...
We design a 0:795 approximation algorithm for the Max-Bisection problem restricted to regular graphs. In the case of three regular graphs our results imply an approximation ratio ...
We study the proper learnability of axis-parallel concept classes in the PAC-learning and exactlearning models. These classes include union of boxes, DNF, decision trees and multi...
Abstract. We consider the function ensembles emerging from the construction of Goldreich, Goldwasser and Micali (GGM), when applied to an arbitrary pseudoramdon generator. We show ...