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pro vyhledávání: '"Yin, Longhui"'
In undirected graphs with real non-negative weights, we give a new randomized algorithm for the single-source shortest path (SSSP) problem with running time $O(m\sqrt{\log n \cdot \log\log n})$ in the comparison-addition model. This is the first algo
Externí odkaz:
http://arxiv.org/abs/2307.04139
A $k$-vertex connectivity oracle for undirected $G$ is a data structure that, given $u,v\in V(G)$, reports $\min\{k,\kappa(u,v)\}$, where $\kappa(u,v)$ is the pairwise vertex connectivity between $u,v$. There are three main measures of efficiency: co
Externí odkaz:
http://arxiv.org/abs/2201.00408
Autor:
Pettie, Seth, Yin, Longhui
In this paper we continue a long line of work on representing the cut structure of graphs. We classify the types minimum vertex cuts, and the possible relationships between multiple minimum vertex cuts. As a consequence of these investigations, we ex
Externí odkaz:
http://arxiv.org/abs/2102.06805
Cardinality estimation is perhaps the simplest non-trivial statistical problem that can be solved via sketching. Industrially-deployed sketches like HyperLogLog, MinHash, and PCSA are mergeable, which means that large data sets can be sketched in a d
Externí odkaz:
http://arxiv.org/abs/2008.08739
Akademický článek
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Cardinality estimation is perhaps the simplest non-trivial statistical problem that can be solved via sketching. Industrially-deployed sketches like HyperLogLog, MinHash, and PCSA are mergeable, which means that large data sets can be sketched in a d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd6a4a4f05b8162a9ebc3027ba31b473
Autor:
Zhuohua Zhang, Lingtong Hao, Meili Chen, Cheng Li, Yin Longhui, Chuandong Liu, Lingyan Cao, Zhenguo Xu, Shaoping Ling
Genome variant detection is a challenge task in cancer genome analysis. Current software for variant detection is very time-consuming and in the same time not accurate enough to satisfy the requirements of clinical applications in precision oncology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f13a2679b0cbdca9984417f485792d6