Skip to main content
Side panel
Home
Calendar
More
English (en)
English (en)
Français (fr)
You are currently using guest access
Log in
Home
Calendar
Expand all
Collapse all
Open course index
CS-526
23 - 24 February
1. PAC learning framework
1. PAC learning framework
Completion requirements
Click
PAC learning.pdf
link to view the file.
◄ Discussion and questions
Jump to...
Jump to...
Announcements
Discussion and questions
1. Finite classes and uniform convergence
2. No free lunch theorem
extrahmw-Hoeffding.pdf
Learning infinite classes (video 1h45)
Learning infinite classes I
Learning infinite classes II (VCdim)
solution 1
solution 2
Bias-variance tradeoff and double descent: Part I
Moore Penrose hmw
Moore Penrose solution
Homework 3
solution-hmw-3
Double descent part II
Two models of weak features by Belkin, Hsu, Xu
Homework 4 (extra hmw on VC dimension)
Homework 5 (hmw on regression and double descent)
Solution Homework 4
Homework 5 solution
Gradient descent
Stochastic gradient descent
homework 6
solution hmw 6
Midterm with solution
Midterm
Mean field approach for two layer NNs part I
Lecture on two layer neural networks (by Andrea Montanari)
homework-7-2026 Part 1
tensor lect 5
tensor lect 5 cont
1. Finite classes and uniform convergence ►
Contact
EPFL CH-1015 Lausanne
+41 21 693 11 11
Follow the pulses of EPFL on social networks
Accessibility
Legal notice
Privacy policy
© 2023 EPFL, all rights reserved
