91 search results - page 11 / 19 » The Data Stream Space Complexity of Cascaded Norms |
116
Voted
KDD
2007
ACM
16 years 2 days ago
2007
ACM
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
103
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COCO
2009
Springer
15 years 6 months ago
2009
Springer
—The Gap-Hamming-Distance problem arose in the context of proving space lower bounds for a number of key problems in the data stream model. In this problem, Alice and Bob have to...
110
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SDM
2007
SIAM
15 years 1 months ago
2007
SIAM
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
PODS
2010
ACM
15 years 4 months ago
2010
ACM
A fundamental problem in data management is to draw a sample of a large data set, for approximate query answering, selectivity estimation, and query planning. With large, streamin...
110
Voted
SODA
2008
ACM
15 years 1 months ago
2008
ACM
A common approach for dealing with large data sets is to stream over the input in one pass, and perform computations using sublinear resources. For truly massive data sets, howeve...