Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Jiashun Jin"'
Publikováno v:
Frontiers in Genetics, Vol 14 (2023)
Subject clustering (i.e., the use of measured features to cluster subjects, such as patients or cells, into multiple groups) is a problem of significant interest. In recent years, many approaches have been proposed, among which unsupervised deep lear
Externí odkaz:
https://doaj.org/article/3ba783a0568346f3b3916e972f51b110
Autor:
Stephen E. Fienberg, Jiashun Jin
Publikováno v:
The Journal of Privacy and Confidentiality, Vol 4, Iss 1 (2012)
We focus on the problem of multi-party data sharing in high dimensional data settings where the number of measured features (or the dimension) p is frequently much larger than the number of subjects (or the sample size) n, the so-called p >> n scenar
Externí odkaz:
https://doaj.org/article/56a1b3afc97b4d35a004519bf05b238a
Autor:
Zheng Tracy Ke, Jiashun Jin
Publikováno v:
Stat. 12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64ba2dc7a6366615d39cb0e1c2333c7d
https://doi.org/10.1002/sta4.545
https://doi.org/10.1002/sta4.545
Publikováno v:
Journal of Business & Economic Statistics. 40:499-504
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::18d81d59a86dfde9ab36440e30cca6e5
https://doi.org/10.1080/07350015.2022.2055358
https://doi.org/10.1080/07350015.2022.2055358
We collected and cleaned a large data set on publications in statistics. The data set consists of the coauthor relationships and citation relationships of 83, 331 papers published in 36 representative journals in statistics, probability, and machine
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::098e2532d4e5d9fd80b1f9afe75df237
http://arxiv.org/abs/2204.11194
http://arxiv.org/abs/2204.11194
Publikováno v:
IEEE Transactions on Signal Processing. 68:1021-1033
For detecting weak and sparse signals by a set of $n$ input $p$ -values, the Higher Criticism (HC) type statistics, the Berk-Jones (B-J) type statistics, and the phi-divergence statistics have the equivalent asymptotic optimality as $n$ goes to infin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed0b4cb7d00266011a57f81e5195b3a3
https://doi.org/10.1109/tsp.2020.2967179
https://doi.org/10.1109/tsp.2020.2967179
Publikováno v:
Stat; Dec2022, Vol. 11 Issue 1, p1-12, 12p
The screening testing is an effective tool to control the early spread of an infectious disease such as COVID-19. When the total testing capacity is limited, we aim to optimally allocate testing resources among n counties. We build a (weighted) commu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28c5f07828eff2375ad9d13f1e423155
Given a symmetric social network, we are interested in testing whether it has only one community or multiple communities. The desired tests should (a) accommodate severe degree heterogeneity, (b) accommodate mixed-memberships, (c) have a tractable nu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::754785c3de855a330cf54676af40fe1f
A network may have weak signals and severe degree heterogeneity, and may be very sparse in one occurrence but very dense in another. SCORE (Ann. Statist. 43, 57–89, 2015) is a recent approach to network community detection. It accommodates severe d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65eb55298aa22bec58e7f9d6cd032263
http://arxiv.org/abs/1811.05927
http://arxiv.org/abs/1811.05927