Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Biswanath Panda"'
Publikováno v:
Proceedings of the VLDB Endowment. 6:1298-1301
The formulation of hypotheses based on patterns found in data is an essential component of scientific discovery. As larger and richer data sets become available, new scalable and user-friendly tools for scientific discovery through data analysis are
Autor:
Biswanath Panda, Ashish Dutta
Publikováno v:
Materials & Design (1980-2015). 31:2471-2477
Four-bar mechanisms traditionally are made of rigid links and they are used for path, motion or function generation. Actively changing the length of the rocker in a crank rocker four-bar mechanism results in the tip of the rocker following a closed p
Publikováno v:
Proceedings of the VLDB Endowment. 2:1426-1437
Classification and regression tree learning on massive datasets is a common data mining task at Google, yet many state of the art tree learning algorithms require training data to reside in memory on a single machine. While more scalable implementati
Publikováno v:
Proceedings of the VLDB Endowment. 1:1476-1479
Archived web data is a great resource for scientific research, but poses serious challenges in data processing and management. We demonstrate the Web Lab Collaboration Server , a platform and service for large-scale collaborative web data analysis in
Autor:
Roberto J. Bayardo, Biswanath Panda
Publikováno v:
Proceedings of the 2011 SIAM International Conference on Data Mining.
Publikováno v:
ICDE
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key for future scientific breakthroughs. Unfortunately, deriving knowledge
Publikováno v:
Encyclopedia of Database Systems ISBN: 9781489979933
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82766979a7190ce2ab7dd457f3a17d4d
https://doi.org/10.1007/978-0-387-39940-9_1289
https://doi.org/10.1007/978-0-387-39940-9_1289
Publikováno v:
ICDM
We address a new learning problem where the goal is to build a predictive model that minimizes prediction time (the time taken to make a prediction) subject to a constraint on model accuracy. Our solution is a generic framework that leverages existin
Autor:
Mingsheng Hong, Mohit Thatte, Joel Ossher, Walker White, Lars Brenna, Biswanath Panda, Alan Demers, Mirek Riedewald, Johannes Gehrke
Publikováno v:
SIGMOD Conference
We propose a demonstration of Cayuga, a complex event monitoring system for high speed data streams. Our demonstration will show Cayuga applied to monitoring Web feeds; the demo will illustrate the expressiveness of the Cayuga query language, the sca