LFD Book Forum  

Go Back   LFD Book Forum > Book Feedback - Learning From Data > Chapter 3 - The Linear Model

Thread Tools Display Modes
Prev Previous Post   Next Post Next
Old 10-12-2012, 09:41 AM
rpistu rpistu is offline
Join Date: Oct 2012
Posts: 10
Default About the Problem 3.17b

I donít quite understand the Problem 3.17b. What the meaning of minimize E1 over all possible (∆u, ∆v). Instead, I think it should minimize E(u+∆u,v+∆v), starting from the point (u,v)=(0,0). Is the optimal column vector [∆u,∆v]T is corresponding to the vt in the gradient descent algorithm (here, as the problem said, it is -∆E(u,v)), the norm ||(∆u,∆v)||=0.5 corresponding to the step size ɧ, and (u,v) corresponding to the weight vector w? Then, what the meaning of compute the optimal (∆u, ∆v)?
Reply With Quote

Thread Tools
Display Modes

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off

Forum Jump

All times are GMT -7. The time now is 04:56 AM.

Powered by vBulletin® Version 3.8.3
Copyright ©2000 - 2021, Jelsoft Enterprises Ltd.
The contents of this forum are to be used ONLY by readers of the Learning From Data book by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin, and participants in the Learning From Data MOOC by Yaser S. Abu-Mostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.