Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Ashwin Lall"'
Publikováno v:
The VLDB Journal. 29:147-175
When faced with a database containing millions of tuples, a user may be only interested in a (typically much) smaller representative subset. Recently, a query called the regret minimization query was proposed toward this purpose to create such a subs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f885cb30ee18267aa77f05fde1bd916
https://doi.org/10.1007/s00778-019-00570-z
https://doi.org/10.1007/s00778-019-00570-z
Autor:
Ashwin Lall
Mathematical Foundations of Computer Science introduces students to the discrete mathematics needed later in their Computer Science coursework with theory of computation topics interleaved throughout. Students learn about mathematical concepts just i
Publikováno v:
SIGMOD Conference
When faced with a database containing millions of tuples, an end user might be only interested in finding his/her (close to) favorite tuple in the database. Recently, a regret minimization query was proposed to obtain a small subset from the database
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56bbd563d2c6dfd632d2b1e74f9dc032
https://doi.org/10.1145/3299869.3300068
https://doi.org/10.1145/3299869.3300068
Publikováno v:
SIGMOD Conference
Extracting interesting tuples from a large database is an important problem in multi-criteria decision making. Two representative queries were proposed in the literature: top- k queries and skyline queries. A top- k query requires users to specify th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e592dedb658b57e20a8f3c2f7bf5c84e
https://doi.org/10.1145/3183713.3196903
https://doi.org/10.1145/3183713.3196903
Publikováno v:
Proceedings of the VLDB Endowment. 8:2098-2109
In exploring representative databases, a primary issue has been finding accurate models of user preferences. Given this, our work generalizes the method of regret minimization as proposed by Nanongkai et al. to include nonlinear utility functions. Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55781946167d14a658ed75ebc09abbf3
https://doi.org/10.14778/2831360.2831364
https://doi.org/10.14778/2831360.2831364
Publikováno v:
Proceedings of the VLDB Endowment. 3:1114-1124
We propose the k -representative regret minimization query ( k -regret) as an operation to support multi-criteria decision making. Like top- k , the k -regret query assumes that users have some utility or scoring functions; however, it never asks the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0dadfabdd5dd843f4e1046fc15d2df0
https://doi.org/10.14778/1920841.1920980
https://doi.org/10.14778/1920841.1920980
Publikováno v:
Proceedings of the VLDB Endowment. 2:85-96
We consider external algorithms for skyline computation without pre-processing. Our goal is to develop an algorithm with a good worst case guarantee while performing well on average. Due to the nature of disks, it is desirable that such algorithms ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6383adfdfc6254d0e1f30a2547b1e561
https://doi.org/10.14778/1687627.1687638
https://doi.org/10.14778/1687627.1687638
Autor:
Ashwin Lall
Publikováno v:
IEEE BigData
We propose space-efficient algorithms for performing the Kolmogorov-Smirnov test on streaming data. The Kolmogorov-Smirnov test is a non-parametric test for measuring the strength of a hypothesis that some data is drawn from a fixed distribution (one
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16d062d0869ef1aaade5874ae8b63a8c
https://doi.org/10.1109/bigdata.2015.7363746
https://doi.org/10.1109/bigdata.2015.7363746
Publikováno v:
SIGMETRICS
Viral marketing is a powerful tool for online advertising and sales because it exploits the influence people have on one another. While this marketing technique has been beneficial for advertisers, it has not been shown how the social network provide
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::308b09cc575ba31591da07ff94d714b9
https://doi.org/10.1145/2745844.2745853
https://doi.org/10.1145/2745844.2745853
Publikováno v:
SIGMETRICS/Performance
Using entropy of traffic distributions has been shown to aid a wide variety of network monitoring applications such as anomaly detection, clustering to reveal interesting patterns, and traffic classification. However, realizing this potential benefit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56df4998dced8725dc08bf7928e433da
https://doi.org/10.1145/1140103.1140295
https://doi.org/10.1145/1140103.1140295