We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...
Abstract. We study the space complexity of randomized streaming algorithms that provide one-sided approximation guarantees; e.g., the algorithm always returns an overestimate of th...
In this paper we relate a number of parsing algorithms which have been developed in very different areas of parsing theory, and which include deterministic algorithms, tabular alg...
We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachythera...
Natasa Milickovic, Michael Lahanas, Dimos Baltas, ...
Abstract— For the multi-robot coverage problem deterministic deliberative as well as probabilistic approaches have been proposed. Whereas deterministic approaches usually provide...
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...
We consider the problem of maintaining approximate counts and quantiles over fixed- and variablesize sliding windows in limited space. For quantiles, we present deterministic algo...