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Sampling algorithms in a stream operator
Proceedings of the 2005 ACM SIGMOD international conference on Management of data, 2005Complex queries over high speed data streams often need to rely on approximations to keep up with their input. The research community has developed a rich literature on approximate streaming algorithms for this application. Many of these algorithms produce samples of the input stream, providing better properties than conventional random sampling.
Theodore Johnson +2 more
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ACM SIGMOD Record, 2014
Over the last decade, there has been considerable interest in designing algorithms for processing massive graphs in the data stream model. The original motivation was two-fold: a) in many applications, the dynamic graphs that arise are too large to be stored in the main memory of a single machine and b) considering graph problems yields new insights ...
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Over the last decade, there has been considerable interest in designing algorithms for processing massive graphs in the data stream model. The original motivation was two-fold: a) in many applications, the dynamic graphs that arise are too large to be stored in the main memory of a single machine and b) considering graph problems yields new insights ...
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Framework for stream learning algorithms
International Journal of Computational Intelligence Studies, 2012Stream learning algorithms learn decision models that continuously evolve over time, run in resource-aware environments, detect and react to changes in the environment generating data. The model should perform well on both training and unseen data and has to give the best possible results in minimum resources.
Archana B. Patil, Vahida Attar
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Fast greedy algorithms in mapreduce and streaming
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures, 2013Greedy algorithms are practitioners’ best friends—they are intuitive, are simple to implement, and often lead to very good solutions. However, implementing greedy algorithms in a distributed setting is challenging since the greedy choice is inherently sequential, and it is not clear how to take advantage of the extra processing power.
Ravi Kumar 0001 +3 more
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Distributed streams algorithms for sliding windows
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Phillip B. Gibbons, Srikanta Tirthapura
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Streaming Algorithms for Data in Motion
2007We propose two new data stream models: the reset model and the delta model, motivated by applications to databases, and to tracking the location of spatial points. We present algorithms for several problems that fit within the stream constraint of polylogarithmic space and time. These include tracking the "extent" of the points and Lp sampling.
Michael Hoffmann 0002 +2 more
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Interactive algorithms: pool, stream and precognitive stream
J. Mach. Learn. Res., 2017Summary: We consider interactive algorithms in the pool-based setting, and in the stream-based setting. Interactive algorithms observe suggested elements (representing actions or queries), and interactively select some of them and receive responses. Pool-based algorithms can select elements at any order, while stream-based algorithms observe elements ...
Sivan Sabato, Tom Hess
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GEOMETRIC STREAMING ALGORITHM WITH A SORTING PRIMITIVE
International Journal of Computational Geometry & Applications, 2007We solve several fundamental geometric problems under a new streaming model recently proposed by Ruhl et al.2,15In this model, in one pass the input stream can be scanned to generate an output stream or be sorted based on a user-defined comparator; all intermediate streams must be of size O(n).
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Streaming Algorithms for Geometric Problems
2004Computing over data streams is a recent phenomenon that is of growing interest in many areas of computer science, including databases, computer networks and theory of algorithms. In this scenario, it is assumed that the algorithm sees the elements of the input one-by-one in arbitrary order, and needs to compute a certain function of the input. However,
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An Optimal Streaming Algorithm for Submodular Maximization with a Cardinality Constraint
Mathematics of Operations Research, 2022Moran Feldman, Alina Ene, Huy L Nguyen
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