I have been reading Stephen Boyd's book Convex Optimization and I have learned to form various problems like LP, QP, QCQP, SOCP or SDPs. I also learned about formulating SVM for classification problem as optimization problem.
Now I am reading about Gradient Methods, Newton's method, etc...
I am trying to understand the difference between L1 vs. L2 regularization in OLS. I understand the concept of center of ellipsoid being the optimal solution and ellipse itself being contours of constant squared errors. And when we use L2 regularization we introduce a spherical constraint on...
Hi,
I am reading Convex Optimization from Stephen Boyd's book on my own and I am stuck at math he mentions on Pg. 157 of his book which can be found here.
How does he write the following:
sup{uTP^{T}_{i}x | ||u||2 ≤ 1} = ||P^{T}_{i}x||2
Thanks guys
Hi,
I am new to Math so I am trying to get some intuition.
Let's say I have a matrix A of n x n and a vector B of n x 1 what is the difference between A x B and A' x B?
Thanks
Hi
What is the angle between a vector (e.g. a row vector A) and it's transpose (a column vector) ? I know what transpose means mathematically but what is the intuition?
Thanks guys
Hi,
I am starting to learn real math I would say for first time in life. I have come across this function:
f(x) = maxi(xi) - mini(xi)
The domain is R.
Does the above function mean f(x) = 0 since for for x in R max and min of x would be x itself.
Hence it is convex as for any...
Hi,
I have two questions.
(1) I am trying to understand how the following function is quasi-linear:
f = min(1/2,x,x^2)
For it to be quasi linear it has to be quasi convex and quasi concave at same time.
(2) I think the reason the above function is not concave is cause on a...