A few Talks and Places

Slides

  • MLSS London 2018. Modern Analysis of kNN (Slides, Part 1 and Part 2)

  • ICML 2018, Tutorial (with Sanjoy Dasgupta): Understanding Your Neighbors (Slides, Part 1 and Part 2)

  • Transfer Learning (discrepancy measures, and limits of transfer). (Slides)

  • Density-based clustering (mode seeking on kNN graphs). (Slides)

  • Adaptivity (manifold, sparsity, smoothness, noise). (Slides)

  • Active Learning (regimes of performance under smoothness and noise). (Slides)

Places

  • Yale, Statistics and Data Science Seminar. October 2020.

  • Standford, Statistics Seminar. September 2020.

  • UW-Madison, SILO Seminar. October 2020.

  • NYU, Courant Institute, Math and Data Seminar (MaD). July 2020.

  • IAS, Special year on ML, Seminar. March 2020.

  • UCLA, IPAM Workshop on “Validation and Guarantees in Learning Physical Models:”. November 2019.

  • University of Michigan, Statistics Seminar. October 2019.

  • MIT Statistics Seminar. September 2019.

  • STOC 2019, Workshop on Data Science Through a Geometric Lens. June 2019

  • UC Davis, Peter Hall Conference. May 19.

  • Deep Learning Indaba 2019, Nairobi, Kenya. August 2019.

  • Machine Learning Summer School (MLSS), London. July 2019.

  • Harvard, Statistics Seminar. October 2018.

  • MIT, Brain Seminar. October 2018.

  • ICML 2018 Tutorial on kNN, Stockholm, Sweden. July 2018.

  • Columbia University, Statistics Seminar. Jan 2018.

  • Google Research, New York. October 2017.

  • Cornell University, Center for Applied Mathematics. September 2017.

  • Daghstul Workshop on Foundations of Unsupervised Learning. September 2016.

  • Duke University, Fuqua, Decision Sciences. October 2016.

  • Machine Learning Summer School (MLSS), Cadiz. May 2016.

  • New York University, Courant Institute. February 2016.

  • University of Pennsylvania, Wharton School, Statistics Seminar. September 2015.

  • CIRM Workshop on Mathematical Statistics (Luminy, France). December 2014.

  • CAL IT2, Information Theory and Applications Workshop. February 2014, 2013, 2017.

  • Carnegie Mellon University, Statistics Seminar. October 2013.

  • ETH (Swiss Federal Institute of Technology) Zurich, ML group. April 2013.

  • Weierstrass Institute for Applied Analysis and Stochastics. November 2011.

  • Foundations of Computational Mathematics, Learning Theory Workshop. June 2011.