About the Problem 3.17b
I don’t 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)?

Re: About the Problem 3.17b
Yes, E1 is a function of ∆u, ∆v, but it is also a function of u, v. Then, what is the u, v in this function? Still use (0, 0) as part (a) said? Also, what is the ininital value of ∆u, ∆v? In the textbook, it sets w to w(0) at step 0.
Further, does the norm (∆u,∆v)=0.5 means that for each iteration we should ensure that the values of ∆u,∆v meet this resuirements? Another point is that in textbook, we need specify the step size ɧ. However, we could not see any information about the step size. I don't quite understand the description of the question (Problem 3.17b), so I have so many questions. Could you probably clarify it for me? Quote:

Re: About the Problem 3.17b
Yes, in this problem you can use (u,v)=(0,0) from part (a).
(∆u,∆v)=0.5 means that the step size . In the chapter we considered two step sizes. First where the step size was fixed at . Second where the step size is proportional to the norm of the gradient. Here, for part (b) the step size is fixed at 0.5. Quote:

Re: About the Problem 3.17b
I have almost understund the problem. But still have a question that what the meaning of the resulting of E(u+∆u,v+∆v) in Part (b), (ei), and (eii). Is it a number or a formula?
Also what the difference of the two parts of (e). One is to minimize E2, the other is to minimize E(u+∆u,v+∆v). So, what the difference of those two? Quote:

Re: About the Problem 3.17b

All times are GMT 7. The time now is 08:17 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. AbuMostafa, Malik MagdonIsmail, and HsuanTien Lin, and participants in the Learning From Data MOOC by Yaser S. AbuMostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.