Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Vapnik–Chervonenkis Theory"'
Autor:
Nobel, Andrew
Publikováno v:
The Annals of Statistics, 1996 Jun 01. 24(3), 1084-1105.
Externí odkaz:
https://www.jstor.org/stable/2242583
Akademický článek
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Publikováno v:
Scopus-Elsevier
Support Vector Machines (SVMs) are a state-of-the-art and powerful learning algorithm that can effectively solve many real world problems. SVMs are the transposition of the Vapnik–Chervonenkis (VC) theory into a learning algorithm. In this paper, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65a0f711eb5a1659c783a01a7b3f601d
https://doi.org/10.1016/j.neucom.2018.10.087
https://doi.org/10.1016/j.neucom.2018.10.087
Autor:
Saptarshi Chakraborty, Swagatam Das
Publikováno v:
Statistics & Probability Letters. 175:109102
Bi-clustering refers to the task of partitioning the rows and columns of a data matrix simultaneously. Although empirically useful, the theoretical aspects of bi-clustering techniques have not been studied in-depth. We present a framework for investi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1677ce32b764f4c9b2d55eee8feb7440
https://doi.org/10.1016/j.spl.2021.109102
https://doi.org/10.1016/j.spl.2021.109102
Publikováno v:
DSAA
other univ website
other univ website
© 2019 IEEE. Recently, there have been several proposals to develop visual recommendation systems. The most advanced systems aim to recommend visualizations, which help users to find new correlations or identify an interesting deviation based on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70b20b8e2b222114595781e094fbd918
https://doi.org/10.1109/dsaa.2019.00039
https://doi.org/10.1109/dsaa.2019.00039
Autor:
Sohail Bahmani, Justin Romberg
Publikováno v:
Electron. J. Statist. 11, no. 2 (2017), 5254-5281
We propose a flexible convex relaxation for the phase retrieval problem that operates in the natural domain of the signal. Therefore, we avoid the prohibitive computational cost associated with “lifting” and semidefinite programming (SDP) in meth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4aba57d7f49f21b6b0f9421126587b6
https://projecteuclid.org/euclid.ejs/1513306873
https://projecteuclid.org/euclid.ejs/1513306873
Publikováno v:
Cognitive Computation. 9:18-42
Big social data analysis is the area of research focusing on collecting, examining, and processing large multi-modal and multi-source datasets in order to discover patterns/correlations and extract information from the Social Web. This is usually acc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::820076197a53d38909546da63df2dbbc
https://doi.org/10.1007/s12559-016-9433-5
https://doi.org/10.1007/s12559-016-9433-5
Autor:
Christoph Aistleitner, Aicke Hinrichs
Publikováno v:
Contemporary Computational Mathematics-A Celebration of the 80th Birthday of Ian Sloan ISBN: 9783319724553
In 2004 the second author of the present paper proved that a point set in [0, 1]d which has star-discrepancy at most e must necessarily consist of at least cabsde−1 points. Equivalently, every set of n points in [0, 1]d must have star-discrepancy a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40641b9ba54d3a8e462357c0fc658c9a
https://doi.org/10.1007/978-3-319-72456-0_3
https://doi.org/10.1007/978-3-319-72456-0_3