An approximate membership data structure is a randomized data
structure for representing a set which supports membership
queries. It allows for a small false positive error rate but has
no false negative errors. Such data structures were first
introduced by Bloom in the 1970's, and have since had numerous
applications, ...
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In this work, we continue the examination of the role non-adaptivity} plays in maintaining dynamic data structures, initiated by Brody and Larsen [BL15].. We consider nonadaptive data structures for predecessor search in the w-bit cell probe model. Predecessor search is one of the most well-studied data structure problems. For this ... more >>>
In 2010, Patrascu proposed a dynamic set-disjointness problem, known as the Multiphase problem, as a candidate for proving $polynomial$ lower bounds on the operational time of dynamic data structures. Patrascu conjectured that any data structure for the Multiphase problem must make $n^\epsilon$ cell-probes in either the update or query phase, ... more >>>
Computing kernels for the hitting set problem (the problem of
finding a size-$k$ set that intersects each hyperedge of a
hypergraph) is a well-studied computational problem. For hypergraphs
with $m$ hyperedges, each of size at most~$d$, the best algorithms
can compute kernels of size $O(k^d)$ in ...
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