In case it is helpful, all my optimization videos in a single playlist are located at ruclips.net/p/PLxdnSsBqCrrHo2EYb_sMctU959D-iPybT. You can support this channel via Patreon at www.patreon.com/christopherwlum. Please let me know what you think in the comments. Thanks for watching!
AE 501: Optimization has always been something I've been interested in ever since I got my first taste of it at my internship a year ago, glad we get to dig into the details on it!
AE501: Line minimization is new to me, so I enjoyed this video. When you began to introduce numerically solving for the minimum of alpha, I immediately wondering about the range selection. And of course this was addressed at the end of the video! The interesting thing about this technique is that by choosing a range to search for the minimum of alpha, you essentially turn your unconstrained optimization problem into a constrained one.
A E 501 It really surprised me how quickly the numerical results were able to converge on the point in so few steps for the line minimization step selection as opposed to the diminishing step size. The way that you explained this numerical minimization gave me a new perspective on optimization that I have not seen before. This lecture was very well done, thank you.
Hi foxcatch, I believe I've seen your comments in some of the optimization videos. If you find these videos helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum or via the 'Thanks' button underneath the video. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. Thanks for watching! -Chris
AE 501: Jesse Perez - This is an interesting step size method using a linear technique but I can see how this could be inefficient if our point of interest isn't along the direction picked and an infinite set could make this approach costly as pointed out at 36:52.
AE501: I'm curious why the constraint on alpha is greater than or equal to 0, rather than greater than 0. It's never possible for alpha to be 0 right? If alpha were zero, there would be a minima at the current x_k, which means our algorithm is already at the lowest point on the cost function. Am I missing something?
Hi Nimesh, Thanks for the kind words, I'm glad you enjoyed the video. If you find these videos helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum or via the 'Thanks' button underneath the video. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. I can also answer any questions, provide code, notes, downloads, etc. on Patreon. Thanks for watching! -Chris
Thanks for reaching out, I'm glad you enjoyed the video. Unfortunately I'm unable to respond to questions on RUclips due to the sheer volume of inquiries that I receive. That being said, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum as I'll be able to answer questions there. Given your interest in the topic, I'd love to have you as a Patron as I'm able to talk/interact personally with Patrons. Thanks for watching!
In case it is helpful, all my optimization videos in a single playlist are located at ruclips.net/p/PLxdnSsBqCrrHo2EYb_sMctU959D-iPybT. You can support this channel via Patreon at www.patreon.com/christopherwlum. Please let me know what you think in the comments. Thanks for watching!
AE 501: Optimization has always been something I've been interested in ever since I got my first taste of it at my internship a year ago, glad we get to dig into the details on it!
AE501: I now understand the benefits of Line Minimization for numerical optimization. Great video professor Lum!
AE501: Line minimization is new to me, so I enjoyed this video. When you began to introduce numerically solving for the minimum of alpha, I immediately wondering about the range selection. And of course this was addressed at the end of the video! The interesting thing about this technique is that by choosing a range to search for the minimum of alpha, you essentially turn your unconstrained optimization problem into a constrained one.
Very good observations, it sounds like you have a solid intuitive feel for optimization, this will serve you well in future applications!
AE501: Great video, really good to completely understand the notes.
Great content Sir, beautifully explained!!
A E 501
It really surprised me how quickly the numerical results were able to converge on the point in so few steps for the line minimization step selection as opposed to the diminishing step size. The way that you explained this numerical minimization gave me a new perspective on optimization that I have not seen before. This lecture was very well done, thank you.
Great, I'm glad it was helpful, let me know how the others go!
AE501: Interesting stuff to think about.
another great video!
Hi foxcatch,
I believe I've seen your comments in some of the optimization videos. If you find these videos helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum or via the 'Thanks' button underneath the video. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. Thanks for watching!
-Chris
AE 501: Jesse Perez - This is an interesting step size method using a linear technique but I can see how this could be inefficient if our point of interest isn't along the direction picked and an infinite set could make this approach costly as pointed out at 36:52.
[AE501] Very interesting how this essentially results in nested numerical optimization problems
AE501: Interesting stuff to think about...next stop armijo
Great, keep powering through, you're almost to the end!
AE501: I'm curious why the constraint on alpha is greater than or equal to 0, rather than greater than 0. It's never possible for alpha to be 0 right? If alpha were zero, there would be a minima at the current x_k, which means our algorithm is already at the lowest point on the cost function. Am I missing something?
Hello , Could you please share the Matlab examples Files that you explained in your optimization video series ?
Hi Nimesh,
Thanks for the kind words, I'm glad you enjoyed the video. If you find these videos helpful, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum or via the 'Thanks' button underneath the video. Given your interest in this topic, I'd love to have you a as a Patron as I'm able to talk/interact personally with all Patrons. I can also answer any questions, provide code, notes, downloads, etc. on Patreon. Thanks for watching!
-Chris
Dear Dr. Lum
can I send you a PDE probelm I have question about?
Thanks for reaching out, I'm glad you enjoyed the video. Unfortunately I'm unable to respond to questions on RUclips due to the sheer volume of inquiries that I receive. That being said, I hope you'll consider supporting the channel via Patreon at www.patreon.com/christopherwlum as I'll be able to answer questions there. Given your interest in the topic, I'd love to have you as a Patron as I'm able to talk/interact personally with Patrons. Thanks for watching!
Hello Christopher.