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CS-526
25 - 26 March
Homework 5
Homework 5
Click
LT_HW5 (4).pdf
link to view the file.
◄ Part II - Double descent phenomenon and derivation for the weak features model
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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
Homework 4
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
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
Moore Penrose hmw ►
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