Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...
We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size - two parameters known to bound the complexity...
Kalev Kask, Andrew Gelfand, Lars Otten, Rina Decht...
The main result of this paper is a near-optimal derandomization of the affine homomorphism test of Blum, Luby and Rubinfeld (Journal of Computer and System Sciences, 1993). We sho...
We investigate the problem of local reconstruction, as defined by Saks and Seshadhri (2008), in the context of error correcting codes. The first problem we address is that of me...
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...