Sketching Algorithms
  • Fall 2020

Current offering (Fall 2020)

  • Sketching Algorithms

Related previous offerings

  • Sketching Algorithms for Big Data: Piotr Indyk (MIT), Jelani Nelson (Harvard).
  • Sketching, Streaming, and Sub-linear Space algorithms: Piotr Indyk (MIT).
  • Algorithms for Big Data: Jelani Nelson (Harvard).

Related courses at other schools

  • Algorithmic Techniques for Big Data: Moses Charikar (Stanford).
  • Algorithmic Techniques for Big Data Analysis: Barna Saha (University of Minnesota Twin Cities).
  • Algorithmic Techniques for Massive Data: Alexandr Andoni (Columbia).
  • Algorithms for Big Data: Chandra Chekuri (UIUC).
  • Algorithms for Big Data: David Woodruff (CMU).
  • Algorithms for Big Data: Grigory Yaroslavtsev (UPenn).
  • Algorithms for Modern Data Models: Ashish Goel (Stanford).
  • Data Streams Algorithms: Andrew McGregor (UMass Amherst).
  • Data Stream Algorithms: Amit Chakrabarti (Dartmouth).
  • Dealing with Massive Data: Sergei Vassilvitskii (Columbia).
  • Mining Massive Data Sets: Jure Leskovec (Stanford).
  • Models of Computation for Massive Data: Jeff Phillips (Utah).
  • Randomized Algorithms for Matrices and Data: Michael Mahoney (UC Berkeley).
  • Seminar on Data Streams: Hung Ngo, Atri Rudra (Buffalo).
  • Sublinear Algorithms: Erice Price (UT Austin).
  • Sublinear algorithms: Piotr Indyk, Ronitt Rubinfeld (MIT).
  • Sublinear and streaming algorithms: Paul Beame (University of Washington).
  • The Modern Algorithmic Toolbox: Tim Roughgarden, Gregory Valiant (Stanford).
  • A list of compressed sensing courses, compiled by Igor Carron.

Powered by the Academic theme for Hugo.