Classifying with the kernel K
CS-433 Lectures · 104 · 5 · 29 Dec '20
Hello! I can't understand the passages associated to the topic "Classifying with the kernel K" in l…
Lecture 11 : EM
CS-433 Lectures · 62 · 1 · 29 Dec '20
Hello, I am unsure how to get the update parameters $$\mu_{k}^{(t+1)}$$ , i.e. I try to derive L_…
Logistic regression equation on the first page
CS-433 Lectures · 86 · 5 · 29 Dec '20
Hello, I wanted to ask if the equation in the photo is correct to have y in the power in the den…
text classification using matrix factorization
CS-433 Lectures · 93 · 2 · 29 Dec '20
Hi there :) I was asking myself how to deal with the test set when using matrix factorization. …
Adversarial risk in high dimension
CS-433 Lectures · 121 · 2 · 29 Dec '20
Hello, I have a question regarding adversarial risk in high dimension. Based on the first exampl…
lecture 11 EM kmeans
CS-433 Lectures · 67 · 1 · 29 Dec '20
Hi, I understand that as sigma tends to 0 qkn converges towards zkn. But I don't understand why th…
L2-norm Regularization
CS-433 Lectures · 88 · 2 · 29 Dec '20
Hello, I don't understand clearly why the L2-norm regularization term forces the model to be simpl…
Conclusion of 3.1
CS-433 Exercises · 180 · 5 · 28 Dec '20
How do you get from: $$w = (H + \mu I)^{-1} Hw*= (QLQ^T + \mu I)^{-1} QLQ^Tw*$$ to $$w = Q(L…
exercise lecture 2
CS-433 Lectures · 41 · 1 · 28 Dec '20
Hello, Can you please upload answers to exercise 3 and 4 of lecture 2 (slide 23). Note: the…
Do constants matter in computational complexity ?
CS-433 Exercises · 72 · 2 · 28 Dec '20
For gradient descent, the MSE is given by : $$\frac{-1}{N}X^{T}(y - Xw)$$ Which for me gives…
Serie 10 Problem 2.1 Retrieving delta*
CS-433 Exercises · 195 · 5 · 28 Dec '20
Hi, I have a question for the last exercise serie problem 2.1. I have been able to get the foll…
Convergence : gradient descent 1-param model
CS-433 Lectures · 65 · 1 · 28 Dec '20
How would you prove the convergence of the sequence only for gama in (0;2)? ![Captură de ecran 2…
prove that mean absolute error is convex
CS-433 Lectures · 117 · 2 · 28 Dec '20
Hello, I am struggling a bit to prove that mean absolute error is convex (as asked in lecture 1d…
self-supervised vs unsupervised vs supervised
CS-433 Lectures · 114 · 5 · 28 Dec '20
I have a question regarding text representation learning and what is considered to be supervised or…
Question regarding kernelized ridge regression
CS-433 Lectures · 66 · 1 · 28 Dec '20
Good morning, I was a bit confused by how the expression for $$\alpha^{*}$$ was obtained in the alt…
Subgradients
CS-433 Lectures · 188 · 4 · 28 Dec '20
According to the definition of subgradient $$ \mathcal{L}(\mathbf{u}) \geq \mathcal{L}(\mathbf{…
PCA
CS-433 Lectures · 95 · 3 · 27 Dec '20
Dear TAs, I'm struggling to understand why the following statement is not correct: In PCA, the …
alphas in SVMs
CS-433 Lectures · 89 · 2 · 27 Dec '20
Hi, I was reading over the conditions for alpha in SVM. I understand if it is correctly classifi…
Covariance matrix
CS-433 Lectures · 110 · 3 · 27 Dec '20
Hi, I was going through the course again, and I was wondering why the covariance matrix is posit…
Hard vs Soft Margin SVM interpretation
CS-433 Lectures · 75 · 2 · 26 Dec '20
Hello, I have a doubt about the interpretation I should give to hard/soft margin SVM formulations. …