Lecturer: Yossi Keshet <jkeshet@cs.biu.ac.il>
Teaching assistant: Roni Cheriyak <advmlcourses+adv@gmail.com>
Zoom link to the live meeting is https://us02web.zoom.us/j/86973527069?pwd=UkFMVkxzRFR2cUR6R08zNjRBMWJMUT09
Deep learning theory 1: What is
machine learning theory? What are generalization bounds?
Definitions and introduction.
Recording of the lecture held on 8/3/2021.
Deep learning theory 2: Re-thinking
generalization; Robustness and generalization; Stability and
generalization
The lecture is based on the following resources:
- Zhang, Bengio, Hardt, Recht and Vinyals, Understanding deep learning requires
rethinking generalization, 2017
- Jakubovitz, Giryes, and Rodrigues, Generalization Error in Deep Learning,
2018
- Xu and Mannor, Robustness and
Generalization, 2012
- The blog of Mostafa Samir
(three parts), 2018
Recording of the lecture held on 15/3/2021.
Deep learning theory 3: PAC-Bayes
theory and generalization
The lecture is based on the following resources:
- Belkin, Hsu, Ma, and Mandal, Reconciling modern machine-learning practice and the classical biasâ€“variance trade-off, 2019
- Jiang, Neyshabur, Mobahi, Krishnan, and Bengio, Fantastic Generalization Measures and Where to Find Them, 2019
Recording of the lecture held on 6/4/2021.