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Srikanta Tirthapura

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“Parallel Streaming Random Sampling” accepted to Europar 2019

May 8, 2019 By snt

Our work on parallel algorithms for streaming random sampling has been accepted to Europar 2019. This presents parallel methods for a fundamental problem — reservoir sampling from a stream, and its variants, including sliding window. The algorithms are work-efficient and have low-depth (i.e. they are highly parallel). Parallelizing the “seemingly sequential” steps of these algorithms has some twists to it. Please check out our paper ( will post the final version soon) —  joint work with Kanat Tangwongsan of Mahidol University, Thailand.

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Recent News

  • Tutorial at the Web Conference “Subgraph counting: the methods behind the madness” May 15, 2019
  • “Parallel Streaming Random Sampling” accepted to Europar 2019 May 8, 2019
  • “Incremental Maintenance of Maximal Cliques in a Dynamic Graph” accepted to the VLDB Journal April 2, 2019
  • Congrats, Dr. Apurba Das March 15, 2019
  • “Weighted Reservoir Sampling from Distributed Streams” accepted to PODS 2019 March 11, 2019
  • Tutorial on Subgraph Counting at The Web Conference 2019 February 12, 2019
  • “Stratified Random Sampling over Streaming and Stored Data” accepted to EDBT 2019 November 26, 2018
  • “Enumerating Top-k Quasi-Cliques” accepted to IEEE Bigdata 2018 October 22, 2018
  • “Shared-Memory Parallel Maximal Clique Enumeration” accepted to HiPC 2018 September 9, 2018
  • “Variance-Reduced Stochastic Gradient Descent on Streaming Data” accepted to NIPS 2018 September 7, 2018

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