Messages

Published June 10, 2024 3:00 PM
Published May 14, 2024 3:55 PM

Are now on the course page, separate folders. [and Schedule]

I'll go through slides tomorrow, starting 09.15

Published May 12, 2024 12:48 PM

The expected value of the average of  weights  is  1

(Not the sum of weights)  Thanks to  Alfonzo.

Published Apr. 23, 2024 4:10 PM

Tomorrow I will start by going through the exercise at 09.15.

After this I will be available for questions in NHA 107 until 12.00

Published Apr. 14, 2024 6:18 PM

Two corrections to original pdf are made, new posted:

Corrections on:

1) Page 22 (old P20):
    E
(\mu_k^2)=m_k^2+s_k^2

...

Published Apr. 10, 2024 10:13 AM

I have now commented on all   exercises that has been handed in for part 1. If you open in adobe acrobat you can read the comments.

Published Mar. 20, 2024 1:29 AM

21.03 2024 12.15-13.30 in NHA 107

Published Feb. 27, 2024 6:40 PM

No lecture Wednesday 6th of March 

 

 

Published Feb. 21, 2024 8:59 AM

22.2.2024 12.15 - 13.30 

In room 107

Published Feb. 20, 2024 3:03 PM

Se below on the page

Published Feb. 12, 2024 9:45 AM

1) In the Lecture note it was written that Traveling salesperson problem was NP, it is as formulated in the lecture NP-Hard  (in some discrete formulations it is NP-complete) 

2) The code which shows the local search "Greedy" in ex 3.1, can be regarded as "too greedy". It updates the parameter at once when it finds an improvement, rather than searching through complete the neighborhood first. I have added code that does the search of the complete neighborhood first for comparison. 

 

Published Jan. 18, 2024 1:07 PM

  9.15-10.00:  Exercise.
10.15 -12 : Lectures

We will discuss the ordering in class.

 

Published Jan. 18, 2024 12:43 AM

In general the  the relation "I=J" is for the canonical link function.
 

Published Jan. 18, 2024 12:32 AM

From the lecture today

Published Jan. 4, 2024 4:24 PM

* Introduction to the course
* Inform/Discuss how lectures & exercises are organized
* Chapter 1 in course book (Review)
* Chapter 2 (Optimization)