Spring 2022
This term the Information Theory, Machine Learning and Statistics Seminar focuses on generalization
in machine learning, privacy and related topics. The seminar consists of a series of two-hours talks
aimed at graduate students and researchers with a basic knowledge of information theory and machine
learning. Talks are unusually long to allow speakers to discuss their results and proof techniques in detail.
Sessions take place every other Friday from 9am to 11am (CDT) over Zoom.
(Access link: https://cuaed-unam.zoom.us/j/83608728443)
To be added to the seminar mailing list, please send an email to mario.diaz@sigma.iimas.unam.mx
List of Speakers
Date
Speaker
Title
25/Mar
Tyler Sypherd
Arizona State UniversityBeing properly improper
08/Apr
Hrayr Harutyunyan
University of Southern CaliforniaInformation-theoretic generalization bounds for black-box learning algorithms
22/Apr
Shahab Asoodeh
McMaster UniversityPOSTPONED
06/May
Wael Alghamdi
Harvard UniversitySchrodinger's cactus: optimal differential privacy mechanisms in the large-composition regime
20/May
Shahab Asoodeh
McMaster UniversityContraction coefficients of Markov kernels under local differential privacy
Previous Schedules
[Fall 2021]
[Spring 2021]
[Fall 2020]
Last update: May 3, 2022