• Publications
  • Influence
Optimizing linear counting queries under differential privacy
TLDR
We propose the matrix mechanism, a new algorithm for answering a workload of predicate counting queries, and investigate the problem of computing the optimal query strategy in support of a given workload. Expand
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Analyzing graph structure via linear measurements
TLDR
We initiate the study of graph sketching, i.e., algorithms that use a limited number of linear measurements of a representation of a graph to determine the properties of the graph. Expand
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On graph problems in a semi-streaming model
TLDR
We formalize a potentially rich new streaming model, the semi-streaming model, that we believe is necessary for the fruitful study of efficient algorithms for solving problems on massive graphs whose edge sets cannot be stored in memory. Expand
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Finding Graph Matchings in Data Streams
  • A. Mcgregor
  • Mathematics, Computer Science
  • APPROX-RANDOM
  • 22 August 2005
TLDR
We present algorithms for finding large graph matchings in the streaming model. Expand
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Graph stream algorithms: a survey
TLDR
We survey the state-of-the-art results; identify general techniques; and highlight some simple algorithms that illustrate basic ideas. Expand
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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 approximations of theExpand
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Approximation algorithms for clustering uncertain data
TLDR
We study the core mining problem of clustering on uncertain data, and define appropriate natural generalizations of standard clustering optimization criteria that generalize both traditional k-center and k-median objectives. Expand
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Reconstructing strings from random traces
TLDR
We are given a collection of m random subsequences (traces) of a string t of length n where each trace is obtained by deleting each bit in the string with probability q. Expand
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Declaring independence via the sketching of sketches
TLDR
We consider the problem of identifying correlations in data streams. Expand
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Graph distances in the streaming model: the value of space
TLDR
We investigate the importance of space when solving problems based on graph distance in the streaming model. Expand
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