Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Henry Pao"'
Autor:
Adam Lopez, Matt Post, Chris Callison-Burch, Jonathan Weese, Juri Ganitkevitch, Narges Ahmidi, Olivia Buzek, Leah Hanson, Beenish Jamil, Matthias Lee, Ya-Ting Lin, Henry Pao, Fatima Rivera, Leili Shahriyari, Debu Sinha, Adam Teichert, Stephen Wampler, Michael Weinberger, Daguang Xu, Lin Yang, Shang Zhao
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 1 (2021)
Externí odkaz:
https://doaj.org/article/fcc4271bd6c941358ade886f00f4b7db
Autor:
Donniell E. Fishkind, Li Chen, Eric W. Bridgeford, Jordan Yoder, Vince Lyzinski, Carey E. Priebe, Keith Levin, Henry Pao
Publikováno v:
Computational Statistics & Data Analysis. 145:106916
Suppose that one particular block in a stochastic block model is of interest, but block labels are only observed for a few of the vertices in the network. Utilizing a graph realized from the model and the observed block labels, the vertex nomination
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5a09f953720adb8a199982e02bcb855
https://doi.org/10.1016/j.csda.2020.106916
https://doi.org/10.1016/j.csda.2020.106916
Autor:
Daniel L. Sussman, Henry Pao, Li Chen, Donniell E. Fishkind, Joshua T. Vogelstein, Youngser Park, Vince Lyzinski, Carey E. Priebe
Publikováno v:
Parallel Computing. 47:70-87
We present a parallelized bijective graph matching algorithm that leverages seeds and is designed to match very large graphs. Our algorithm combines spectral graph embedding with existing state-of-the-art seeded graph matching procedures. We justify
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0ea279ec72dea510e84c61ca9740fb3
https://doi.org/10.1016/j.parco.2015.03.004
https://doi.org/10.1016/j.parco.2015.03.004
Autor:
Ya-Ting Lin, Juri Ganitkevitch, Beaniesh Jamil, Fatima Rivera, Leili Shahriyari, Debu Sinha, Shang Zhao, Stephen Wampler, Narges Ahmidi, Olivia Buzek, Matt Post, Leah Hanson, Adam Lopez, Jonathan Weese, Matthias A. Lee, Lin Yang, Adam R. Teichert, Daguang Xu, Chris Callison-Burch, Michael Weinberger, Henry Pao
Publikováno v:
Transactions of the Association for Computational Linguistics. 1:165-178
Machine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them are best learned by doing. As a centerpiece of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65868c3ecfa46e1bc617035ed1b46244
https://doi.org/10.1162/tacl_a_00218
https://doi.org/10.1162/tacl_a_00218
Publikováno v:
Journal of Computational and Graphical Statistics. 20:395-416
We present a comparative power analysis, via Monte Carlo, of various graph invariants used as statistics for testing graph homogeneity versus a “chatter” alternative—the existence of a local region of excessive activity. Our results indicate th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cbc1d3d97817dee38e60ff49f53321e
https://doi.org/10.1198/jcgs.2010.09004
https://doi.org/10.1198/jcgs.2010.09004
Publikováno v:
Ann. Appl. Stat. 9, no. 3 (2015), 1510-1532
Suppose that a graph is realized from a stochastic block model where one of the blocks is of interest, but many or all of the vertices' block labels are unobserved. The task is to order the vertices with unobserved block labels into a ``nomination li
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f22046f763409af85bcce9666a69c57b
