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...
— Sampling-based motion planners are often used to solve very high-dimensional planning problems. Many recent algorithms use projections of the state space to estimate properties...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
We continue the study of approximating the number of distinct elements in a data stream of length n to within a (1? ) factor. It is known that if the stream may consist of arbitra...