ACM SIGMOD City, Country, Year
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SIGMOD 2020: Accepted Tutorials

  • Automating Exploratory Data Analysis via Machine Learning: An Overview
    Tova Milo (Tel Aviv University); Amit Somech (Tel Aviv University)
  • Crowdsourcing Practice for Efficient Data Labelling: Aggregation, Incremental Relabeling, and Pricing
    Alexey Drutsa (Yandex); Valentina Fedorova (Yandex); Dmitry Ustalov (Yandex); Olga Megorskaya (Yandex); Evfrosiniya Zerminova (Yandex); Daria Baidakova (Yandex)
  • State of the Art and Open Challenges in Natural Language Interfaces to Data
    Fatma Özcan (IBM Research AI); Abdul Quamar (IBM Research AI); Jaydeep Sen (IBM Research AI); Chuan Lei (IBM Research AI); Vasilis Efthymiou (IBM Research AI)
  • Fairness and Bias in Peer Review and other Sociotechnical Intelligent Systems
    Nihar B. Shah (Carnegie Mellon University); Zachary Lipton (Carnegie Mellon University)
  • Le Taureau: Deconstructing the Serverless Landscape & A Look Forward
    Anurag Khandelwal (Yale University); Arun Kejariwal (Facebook Inc.); Karthik Ramasamy (Splunk Inc.)
  • Beyond Analytics: the Evolution of Stream Processing Systems
    Paris Carbone (RISE SICS); Vasiliki Kalavri (Boston University); Marios Fragkoulis (TU Delft); Asterios Katsifodimos (TU Delft)
  • Worst-Case Optimal Joins Meet Top-k: Algorithms, Cost Models and Optimality
    Nikolaos Tziavelis (Northeastern University); Wolfgang Gatterbauer (Northeastern University); Mirek Riedewald (Northeastern University)
  • Key-value Storage Engines
    Stratos Idreos (Harvard University); Mark Callaghan (MongoDB)

Credits
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