Maintaining time-decaying stream aggregates☆
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Maintaining time-decaying stream aggregates
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2019, Pattern RecognitionCitation Excerpt :Xioufis et al. [9] used two windows per label to capture the positive and negative groups of samples. The decay function approach, meanwhile, use weights to mitigate or strengthen the importance of samples based on their age, i.e., the older sample is less important than the new one [35]. The learning model, therefore, can adapt to the changes that appear in the new data.
Multi-label classification via label correlation and first order feature dependance in a data stream
2019, Pattern RecognitionCitation Excerpt :Xioufis et al. [9] used two windows per label to capture the positive and negative group of samples. The decay function strategy, meanwhile, uses weights to mitigate or strengthen the importance of samples based on their ages, i.e. the older sample is less important than the new one [69,70]. The learning model, therefore, can adapt to changes in the newer data.
Sampling Big Ideas in Query Optimization
2023, Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems
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A preliminary version of this paper appeared in: Proc. of the 2003 ACM Symposium on Principles of Database Systems, PODS 2003, ACM, 2003.
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Part of this work was done while the author was at AT&T.