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On the power of randomization in on-line algorithms ...
Against in adaptive adversary, we show that the power of randomization in on-line algorithms is severely limited! We prove the existence of an efficient “simulation” of randomized on-line algorithms by deterministic ones, which is best possible in general. The proof of the upper bound is ...
On the power of randomization in on-line algorithms
On the Power of Randomization in On-Line Algorithms 3 an abstract formulation (called task systems) and a formal definition for the study
Adversary model - Wikipedia
Adversary model (Redirected from Adversary (online algorithm)) In computer science, an online algorithm measures its competitiveness against different adversary models. For deterministic algorithms, the adversary is the same as the adaptive offline adversary. ... 10.1007/BF01294260. External links.
Gábor Tardos - Wikipedia
Gábor Tardos (born 11 July 1964) is a Hungarian mathematician, currently a professor at Central European University and previously a Canada Research Chair at Simon Fraser University.He works mainly in combinatorics and computer science.He is the younger brother of Éva Tardos.
Allan Borodin - Wikipedia
Allan Bertram Borodin (born 1941) is a Canadian-American computer scientist who is a University Professor at the University of Toronto.
About Allan Borodin | Computer scientist, Educator ...
Allan Bertram Borodin (born 1941) is a Canadian-American computer scientist who is a University Professor at the University of Toronto. Biography
(PDF) On the Power of Randomization in On-Line Algorithms.
Against in adaptive adversary, we show that the power of randomization in on-line algorithms is severely limited! We prove the existence of an efficient simulation of randomized on-line algorithms ...
An adaptive probabilistic algorithm for online k -center ...
The \begin{document}$k$\end{document}-center clustering is one of the well-studied clustering problems ...