Zobrazeno 1 - 10
of 157
pro vyhledávání: '"John E Hopcroft"'
Autor:
Xinbing Wang, Huquan Kang, Luoyi Fu, Ling Yao, Jiaxin Ding, Jianghao Wang, Xiaoying Gan, Chenghu Zhou, John E Hopcroft
Publikováno v:
PLoS ONE, Vol 18, Iss 1, p e0279314 (2023)
Scientific literature, as the major medium that carries knowledge between scientists, exhibits explosive growth in the last century. Despite the frequent use of many tangible measures, to quantify the influence of literature from different perspectiv
Externí odkaz:
https://doaj.org/article/0301c1863c474585a7ffd4f4a982b485
Local community detection has attracted much research attention recently, and many methods have been proposed for the single local community detection that finds a community containing the given set of query nodes. However, nodes may belong to severa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e95f64f0782447ddce0e4d39d6fb98f9
Publikováno v:
INFOCOM
While community detection has been one of the cornerstones in network analysis and data science, its opposite, community obfuscation, has received little attention in recent years. With the increasing awareness of data security and privacy protection
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 13:1-30
Community detection is an important information mining task to uncover modular structures in large networks. For increasingly common large network data sets, global community detection is prohibitively expensive, and attention has shifted to methods
Autor:
Bistra Dilkina, Bart Selman, Daniel Freund, Warren B. Powell, Stefano Ermon, Steve Kelling, Angela K. Fuller, Alexander S. Flecker, John S. Selker, Carla P. Gomes, Douglas H. Fisher, Yexiang Xue, Milind Tambe, Mary Lou Zeeman, Fei Fang, Xiaoli Z. Fern, Christopher B. Barrett, Xiaojian Wu, John M. Gregoire, Alan Fern, Zico Kolter, John E. Hopcroft, Daniel Fink, Andrew Farnsworth, David B. Shmoys, Jon M. Conrad, Nicole D. Sintov, Thomas G. Dietterich, Abdul-Aziz Yakubu, Amulya Yadav, Daniel Sheldon, Christopher L. Wood, Weng-Keen Wong
Publikováno v:
Communications of the ACM. 62:56-65
Computer and information scientists join forces with other fields to help solve societal and environmental challenges facing humanity, in pursuit of a sustainable future.
Publikováno v:
Knowledge-Based Systems. 164:459-472
We propose a Locally-Biased Spectral Approximation (LBSA) approach for identifying all latent members of a local community from very few seed members. To reduce the computation complexity, we first apply a fast random walk, personalized PageRank and
Publikováno v:
CVPR
We address the problem of removing undesirable reflections from a single image captured through a glass surface, which is an ill-posed, challenging but practically important problem for photo enhancement. Inspired by iterative structure reduction for