set intersection problemdecentralized distributed algorithmcardinalitysmallest-sized subsettime complexity/ C4240 Programming and algorithm theory C1160 Combinatorial mathematicsSummary: A simple decentralized
If polygon A has n edges and polygon B has m edges, then the number of edge-edge intersection tests is nm, so the algorithm has O(nm) time complexity (quadratic in time). The use of BSP trees reduces the number of comparisons since edges of A on one side of a splitting line need...
^Cristofaro, Emiliano De, Jihye Kim, and Gene Tsudik. "Linear-complexity private set intersection protocols secure in malicious model." International Conference on the Theory and Application of Cryptology and Information Security. Springer, Berlin, Heidelberg, 2010. ^Jarecki, Stanisław, and Xiaomin ...
请看 Python 一些数据结构的时间复杂度TimeComplexity - Python Wikiwiki.python.org/moin/TimeComplex...
Private Set Intersection (PSI) is one of important privacy preserving protocols. Usually, previous PSI is executed by 2-parties, a client and a server, where both a client and a server compute jointly the intersection of their private sets in such a way that at the end only the client ...
Protocols for Private Set Intersection (PSI) are important cryptographic techniques to perform joint operations on datasets in a privacy-preserving way. They allow two parties to compute the intersection of their private sets without revealing any additional information beyond the intersection itself, for...
The intersection is all values that are in this sorted set and each of the other iterables. >>> ss = SortedSet([1, 2, 3, 4, 5]) >>> ss.intersection([4, 5, 6, 7]) SortedSet([4, 5]) Parameters: iterables –iterable arguments Returns: new sorted set intersection...
Private Set Intersection Cardinality that enable Multi-party to privately compute the cardinality of the set intersection without disclosing their own information. It is equivalent to a secure, distributed database query and has many practical applicatio
It is useful because it can perform mathematical set operations such as union, intersection, and difference. Additionally, sets are faster to search than lists or dictionaries because they are implemented using hash tables, which have a constant average-case time complexity for operations such as ...
This paper considers time-space tradeoffs for various set operations. Denoting the time requirement of an algorithm by T and its space requirement by S, it is shown that TS=Ω(n2) for set complementation and TS=Ω(n32) for set intersection, in the R-way branching program model. In the ...