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Ooi, Beng Chin
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Scaling distributed transaction processing and recovery based on dependency logging
Yao C., Zhang M., Lin Q., Ooi B., Xu J. The VLDB Journal: The International Journal on Very Large Data Bases 27(3): 347-368, 2018. Type: Article
Since the beginning of the Computer Age, databases have stored data and applications have used that data. The use of the same data at the same time by different applications is called concurrency, and it may cause problems. Different m...
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Aug 31 2018
epiC: an extensible and scalable system for processing big data
Jiang D., Wu S., Chen G., Ooi B., Tan K., Xu J. The VLDB Journal: The International Journal on Very Large Data Bases 25(1): 3-26, 2016. Type: Article
Addressing the problem of performance while processing big data, the authors propose a new programming model, named epiC, that deals with the problem of data variety, for example when data arrives at the evaluation engine as a mix of s...
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Sep 27 2016
SINGA: putting deep learning in the hands of multimedia users
Wang W., Chen G., Dinh A., Gao J., Ooi B., Tan K., Wang S. MM 2015 (Proceedings of the 23rd Annual ACM Conference on Multimedia, Brisbane, Australia, Oct 26-30, 2015) 25-34, 2015. Type: Proceedings
Deep learning is an aspect of machine learning that attempts, through algorithms, to model complex abstractions in data. A research goal is to create architectures to achieve this with masses of uncharacterized data. This research pape...
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Dec 14 2015
Peer-to-peer computing: principles and applications
Vu Q., Lupu M., Ooi B., Springer Publishing Company, Incorporated, New York, NY, 2009. 317 pp. Type: Book (978-3-642035-13-5)
My stack of peer-to-peer (P2P)-related books is getting higher and higher. When I see yet another title of this kind, I wonder if it is still possible to present it another way. Well, the authors show in their 300-plus-page book that i...
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Mar 29 2010
BORDER: efficient computation of boundary points
Xia C., Hsu W., Lee M., Ooi B. IEEE Transactions on Knowledge and Data Engineering 18(3): 289-303, 2006. Type: Article
When data is collected, it is often clustered in sets that have associated ranges of variables. For example, when environmental data is gathered (to, for instance, determine heavy metal concentrations downwind from a smelter), it is ea...
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Aug 16 2006
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