Skip to main content
Side panel
Home
More
English (en)
English (en)
Français (fr)
You are currently using guest access
Log in
Home
Open course index
CS-526
18 - 19 March
Homework 4
Homework 4
Click
LT_HW4.pdf
link to view the file.
◄ Part I - Bias Viariance Decomposition and Double Descent
Jump to...
Jump to...
Announcements
Discussion and questions
PAC learning framework
Finite classes and uniform convergence
solution 1
No free lunch theorem
extrahmw-Hoeffding.pdf
solution 2
Learning infinite classes I
homework 3 graded
solution-hmw-3-graded
Learning infinite classes II (VCdim)
Part I - Bias Viariance Decomposition and Double Descent
Solution Homework 4
Two models of weak features by Belkin, Hsu, Xu
First graded homework (HW3)
Part II - Double descent phenomenon and derivation for the weak features model
Homework 5
Moore Penrose hmw
Moore Penrose solution
Homework 5 solution
Gradient descent
Stochastic gradient descent
homework 6 graded
solution hmw 6 (graded)
Mean field approach for two layer NNs part I
Mean field approach to two layer NNs part II
Lecture on two layer neural networks (by Andrea Montanari)
Additional Exercises on GD & SGD
Solution to Extra HWs
2nd graded hmw 6
tensor lect 1
tensor lect 1 cont
Homework 7 (Graded)
3rd Graded homework (Homework 7)
homework 11
solution 11
Solution Homework 4 ►
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
