Abstract- This paper presents a new operator for genetic algorithms that enhances their convergence in the case of nonlinear problems with nonlinear equality constraints. The propo...
We consider the problem of private efficient data mining of vertically-partitioned databases. Each of several parties holds a column of a data matrix (a vector) and the parties wan...
Yuval Ishai, Tal Malkin, Martin J. Strauss, Rebecc...
Abstract. In this work we study the tractability of well supported approximate Nash Equilibria (SuppNE in short) in bimatrix games. In view of the apparent intractability of constr...
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
The paper studies the computational complexity and approximation algorithms for a new evolutionary distance between multi-chromosomal genomes introduced recently by Ferretti, Nade...
Bhaskar DasGupta, Tao Jiang, Sampath Kannan, Ming ...