2012
DOI: 10.1080/10618600.2012.657144
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Developing Systems for Real-Time Streaming Analysis

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Cited by 12 publications
(8 citation statements)
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References 27 publications
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“…Effectively, all the prior data, D t−1 are summarized in θ t . This choice means that the computations are bounded by the dimension of θ and the time required to update θ instead of growing as a function of t. Note that this effectively forces users to implement an online policy (Michalak, DuBois, DuBois, Wiel, and Hogden 2012) as the complete dataset D t−1 is not revisited at subsequent interactions. Making a request to StreamingBandit's setreward endpoint containing a JSON object including either the advice_id or a complete description of {x t , a t , p t }, and the reward r t , allows one to update θ t +1 and subsequently to influence the actions selected at t + 1.…”
Section: Basic Usagementioning
confidence: 99%
“…Effectively, all the prior data, D t−1 are summarized in θ t . This choice means that the computations are bounded by the dimension of θ and the time required to update θ instead of growing as a function of t. Note that this effectively forces users to implement an online policy (Michalak, DuBois, DuBois, Wiel, and Hogden 2012) as the complete dataset D t−1 is not revisited at subsequent interactions. Making a request to StreamingBandit's setreward endpoint containing a JSON object including either the advice_id or a complete description of {x t , a t , p t }, and the reward r t , allows one to update θ t +1 and subsequently to influence the actions selected at t + 1.…”
Section: Basic Usagementioning
confidence: 99%
“…This section is aimed at discussion and analysis of existing research on data streams and tries to highlight significant challenges and issues in this domain. In [1] the authors have discussed the issue of power reduction of radio frequency interference (RFI) effect on the high-energy impulses to find it and receive it from different sources. For this the purpose radio astronomy has been used along with an example of Allen Telescope Array (ATA) to collect data.…”
Section: Application Of Data Mining In Crime Detectionmentioning
confidence: 99%
“…Streaming data, consisting of indefinitely and possibly time-evolving sequences, are becoming ubiquitous in many branches of science (Chu et al, 2007;Michalak et al, 2012). The omnipresence of streaming data poses new challenges for statistics and machine learning.…”
Section: Introductionmentioning
confidence: 99%
“…Streaming algorithms provide a computationally efficient way to deal with continuous data streams by summarizing all historic data into a limited set of parameters. With the current growth of available data the development of reliable streaming algorithms whose behavior is well understood is highly important (Michalak et al, 2012). For a more formal description of streaming (or online) learning see Bottou (1998).…”
Section: Introductionmentioning
confidence: 99%