We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
We consider a robust model proposed by Scarf, 1958, for stochastic optimization when only the marginal probabilities of (binary) random variables are given, and the correlation be...
Abstract. We are interested in efficient algorithms for generating random samples from geometric objects such as Riemannian manifolds. As a step in this direction, we consider the ...
Commonly to classify new object in Data Mining one should estimate its similarity with given classes. Function of Rival Similarity (FRiS) is assigned to calculate quantitative mea...
Nikolay G. Zagoruiko, Irina V. Borisova, Vladimir ...