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CS-526
20 - 21 April
homework-7-2026 Part 2
homework-7-2026 Part 2
Completion requirements
Click
homework-7-2026-2.pdf
link to view the file.
◄ Mean field approach to two layer NNs part II
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Discussion and questions
1. PAC learning framework
1. Finite classes and uniform convergence
2. No free lunch theorem
extrahmw-Hoeffding.pdf
Learning infinite classes I
Learning infinite classes II (VCdim)
solution 1
solution 2
Learning infinite classes (video 1h45)
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
solution-7 Part 1
Mean field approach to two layer NNs part II
solution-7 Part 2
tensor lect 1
tensor lect 1 cont
homework 8
solution 8
Video of lecture on tensor decomposition
tensor lect 2
tensor lect 2 cont
Homework 9
tensor lect 5
tensor lect 5 cont
solution-7 Part 2 ►
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