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Analyzing massive data sets has been one of the key motivations for studying streaming algorithms.
A measure of the asymptotic efficiency for tests of a hypothesis based on the sum of observations
H. Chernoff · 1952
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Multi-terminal network flows
R. E. Gomory and T.C. Hu · 1961
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Selection and Sorting with Limited Storage
J. Ian Munro and Mike Paterson · 1980
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A faster algorithm for finding the minimum cut in a graph
Jianxiu Hao and James B. Orlin · 1992
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Global min-cuts in rnc, and other ramifications of a simple min-out algorithm
David R. Karger · 1993
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Random sampling in cut, flow, and network design problems
David R. Karger · 1994
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Approximating s-t minimum cuts in O(n2) time
András A. Benczúr and David R. Karger · 1996
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A new approach to the minimum cut problem
David R. Karger and Clifford Stein · 1996
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Experimental study of minimum cut algorithms
Chandra S. Chekuri, Andrew V. Goldberg, David R. Karger, Matthew S. Levine, and Cliff Stein · 1997
Cited alongside, same era.
Computing on data streams, 1998
M. Henzinger, P. Raghavan, and S. Rajagopalan · 1998
Cited alongside, same era.
The Space Complexity of Approximating the Frequency Moments
Noga Alon, Yossi Matias, and Mario Szegedy · 1999
Cited alongside, same era.
Minimum cuts in near-linear time
David R. Karger · 2000
Cited alongside, same era.
On graph problems in a semi-streaming model
Joan Feigenbaum, Sampath Kannan, Andrew McGregor, Siddharth Suri, and Jian Zhang · 2005
Later among the works it cites.
Finding Graph Matchings in Data Streams
Andrew McGregor · 2005
Later among the works it cites.
Trading off space for passes in graph streaming problems
Camil Demetrescu, Irene Finocchi, and Andrea Ribichini · 2006
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Data streams: Algorithms and Applications
S. Muthukrishnan · 2006
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Graph sparsification by effective resistances
Daniel A. Spielman and Nikhil Srivastava · 2008
Later among the works it cites.
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