We investigate the problem of specification based testing with dense sets of inputs and outputs, in particular with imprecision as they might occur due to errors in measurements, ...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...
We consider the problem of periodic exploration of all nodes in undirected graphs by using a nite state automaton called later a robot. The robot, using a constant number of state...
Leszek Gasieniec, Ralf Klasing, Russell A. Martin,...
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...