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[KIRJA][B] Machine learning for data streams: with practical examples in MOA
A hands-on approach to tasks and techniques in data stream mining and real-time analytics,
with examples in MOA, a popular freely available open-source software framework. Today …
with examples in MOA, a popular freely available open-source software framework. Today …
Synopses for massive data: Samples, histograms, wavelets, sketches
Abstract Methods for Approximate Query Processing (AQP) are essential for dealing with
massive data. They are often the only means of providing interactive response times when …
massive data. They are often the only means of providing interactive response times when …
Data streams: Algorithms and applications
S Muthukrishnan - Foundations and Trends® in Theoretical …, 2005 - nowpublishers.com
In the data stream scenario, input arrives very rapidly and there is limited memory to store
the input. Algorithms have to work with one or few passes over the data, space less than …
the input. Algorithms have to work with one or few passes over the data, space less than …
Stable distributions, pseudorandom generators, embeddings, and data stream computation
P Indyk - Journal of the ACM (JACM), 2006 - dl.acm.org
In this article, we show several results obtained by combining the use of stable distributions
with pseudorandom generators for bounded space. In particular:---We show that, for any …
with pseudorandom generators for bounded space. In particular:---We show that, for any …
Graph sketches: sparsification, spanners, and subgraphs
When processing massive data sets, a core task is to construct synopses of the data. To be
useful, a synopsis data structure should be easy to construct while also yielding good …
useful, a synopsis data structure should be easy to construct while also yielding good …
Differentially private continual releases of streaming frequency moment estimations
The streaming model of computation is a popular approach for working with large-scale
data. In this setting, there is a stream of items and the goal is to compute the desired …
data. In this setting, there is a stream of items and the goal is to compute the desired …
[PDF][PDF] Sketch techniques for approximate query processing
G Cormode - Foundations and Trends in Databases …, 2011 - archive.dimacs.rutgers.edu
Sketch techniques have undergone extensive development within the past few years. They
are especially appropriate for the data streaming scenario, in which large quantities of data …
are especially appropriate for the data streaming scenario, in which large quantities of data …
Tight bounds for adversarially robust streams and sliding windows via difference estimators
In the adversarially robust streaming model, a stream of elements is presented to an
algorithm and is allowed to depend on the output of the algorithm at earlier times during the …
algorithm and is allowed to depend on the output of the algorithm at earlier times during the …
Estimating pagerank on graph streams
This article focuses on computations on large graphs (eg, the web-graph) where the edges
of the graph are presented as a stream. The objective in the streaming model is to use small …
of the graph are presented as a stream. The objective in the streaming model is to use small …
Adversarially robust streaming algorithms via differential privacy
A streaming algorithm is said to be adversarially robust if its accuracy guarantees are
maintained even when the data stream is chosen maliciously, by an adaptive adversary. We …
maintained even when the data stream is chosen maliciously, by an adaptive adversary. We …