Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Kenneth L. Clarkson"'
Autor:
Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler R. Josephson, Joao Goncalves, Kenneth L. Clarkson, Nimrod Megiddo, Bachir El Khadir, Lior Horesh
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-10 (2023)
Abstract Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from
Externí odkaz:
https://doaj.org/article/a071e93910ae4c9eb6c7c38c46e4bf03
Autor:
Kenneth L. Clarkson, Günter Rote
Publikováno v:
Journal of Computational Geometry, Vol 1, Iss 1 (2010)
We are pleased to welcome readers to this inaugural issue of the Journal of Computational Geometry.
Externí odkaz:
https://doaj.org/article/e3e59ffba384400085b4a03664098ab6
Publikováno v:
Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::771f0d490cc0d1773d8e32feafbd452e
https://doi.org/10.1145/3519935.3519988
https://doi.org/10.1145/3519935.3519988
Publikováno v:
Discrete & Computational Geometry. 64:700-733
We study randomized algorithms for constrained optimization, in abstract frameworks that include, in strictly increasing generality: convex programming; LP-type problems; violator spaces; and a setting we introduce, consistent spaces. Such algorithms
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8976fb33dbfb1533cf75d0b8ceb8be25
https://doi.org/10.1007/s00454-020-00193-0
https://doi.org/10.1007/s00454-020-00193-0
Publikováno v:
ICASSP
In recent years, a variety of randomized constructions of sketching matrices have been devised, that have been used in fast algorithms for numerical linear algebra problems, such as least squares regression, low-rank approximation, and the approximat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::160d3ff35d8ba0b82850e5ce1f204053
Autor:
Kenneth L. Clarkson, David P. Woodruff
Publikováno v:
STOC
We design a new distribution over $\poly(r \eps^{-1}) \times n$ matrices $S$ so that for any fixed $n \times d$ matrix $A$ of rank $r$, with probability at least 9/10, $\norm{SAx}_2 = (1 \pm \eps)\norm{Ax}_2$ simultaneously for all $x \in \mathbb{R}^
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85b07a1bf2694fe7f28ea1ea8630e433
https://doi.org/10.1145/3019134
https://doi.org/10.1145/3019134
Publikováno v:
Mathematics, Vol 7, Iss 11, p 1039 (2019)
Mathematics
Volume 7
Issue 11
Mathematics
Volume 7
Issue 11
Foodborne diseases are a longstanding worldwide public health concern. Modeling the transmission pathways of foodborne pathogens accurately and effectively can aid in understanding the spread of pathogens and facilitate decision making for interventi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::091d7253ec76649d1e3a024a2fcbc825
https://www.mdpi.com/2227-7390/7/11/1039
https://www.mdpi.com/2227-7390/7/11/1039
Autor:
Joseph F. Terdiman, Petar Ristoski, Daniel Gruhl, Anna Lisa Gentile, Steve Welch, Kenneth L. Clarkson
Publikováno v:
The Semantic Web ISBN: 9783319934167
ESWC
ESWC
Ontologies are a basic tool to formalize and share knowledge. However, very often the conceptualization of a specific domain depends on the particular user’s needs. We propose a methodology to perform user-centric ontology population that efficient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a393775d6f9b2c678d7c12bc48d66ff
https://doi.org/10.1007/978-3-319-93417-4_8
https://doi.org/10.1007/978-3-319-93417-4_8
Autor:
Anup Pillai, Alexandros Karargyris, Sailesh Conjeti, Hongzhi Wang, Hui Tang, Ehsan Dehghan, Amin Katouzian, Kenneth L. Clarkson, Nassir Navab
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 ISBN: 9783030009366
MICCAI (4)
MICCAI (4)
In this paper, we present a learning based, registration free, atlas ranking technique for selecting outperforming atlases prior to image registration and multi-atlas segmentation (MAS). To this end, we introduce ensemble hashing, where each data (im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::329285311e7d077f1e9295d3f82417d8
https://doi.org/10.1007/978-3-030-00937-3_62
https://doi.org/10.1007/978-3-030-00937-3_62