If you're very busy and don't have enough time to look into full video, please just take a look in this comical moments! 08:50 - People say "Wow, How you did it? GD or SGD?" I'm just looking into them and say "It's not your business."...Which is correct answer in some sense " 24:23 - ...No tuning, nothing, just Huber minimization instead Square minimization... 31:30 - Interesting "Consensus optimization" Some fun moments: 21:19 - "...In this case my opinion is correct. Ha-ha-ha") 43:13 - "...I can pretend to know, but this video is being recorded..." 49:12 - "Q: If you have non-convex problems and we will use solvers that you mentioned. Stephen: It depends....The most accurate technical statements is the following: something happens" 52:32 - Q: Very low voice "you know it's one of criticism of Neural Networks" Stephen: Oh, good! We're here. Neural Network word come up! Just say "Deep Neural Network" ! Q: Solution of Neural Netowrks are probably suboptimal Stephen: No probably, but they are. 55:00 - Stephen: "Please stop! And just ask me "Hey, how can we use it for deep Neural Netowrks" Q: Ha-ha, Ok, how can we use it for deep Neural Netowrks? Stephen: It's a great question! And my answer is I don't know!
This stuff is for few, very specialized people like me and very likely you (given your comment). So standing the fact that I really love the lectures Prof. Boyd gives, how do you think this Video should achieve such a large number?
AI/ML is very popular this days. 1) Maybe if append this work into title and description that I will popup this video in raitings. 2) Also EE263 L1 have been watched e.g. for th-cam.com/video/bf1264iFr-w/w-d-xo.html for 151Kilo times. So it was a reason why e.g. I hoped for video to be popular
If you're very busy and don't have enough time to look into full video, please just take a look in this comical moments!
08:50 - People say "Wow, How you did it? GD or SGD?" I'm just looking into them and say "It's not your business."...Which is correct answer in some sense "
24:23 - ...No tuning, nothing, just Huber minimization instead Square minimization...
31:30 - Interesting "Consensus optimization"
Some fun moments:
21:19 - "...In this case my opinion is correct. Ha-ha-ha")
43:13 - "...I can pretend to know, but this video is being recorded..."
49:12 - "Q: If you have non-convex problems and we will use solvers that you mentioned.
Stephen: It depends....The most accurate technical statements is the following: something happens"
52:32 - Q: Very low voice "you know it's one of criticism of Neural Networks"
Stephen: Oh, good! We're here. Neural Network word come up! Just say "Deep Neural Network" !
Q: Solution of Neural Netowrks are probably suboptimal
Stephen: No probably, but they are.
55:00 - Stephen: "Please stop! And just ask me "Hey, how can we use it for deep Neural Netowrks"
Q: Ha-ha, Ok, how can we use it for deep Neural Netowrks?
Stephen: It's a great question! And my answer is I don't know!
This stuff is for few, very specialized people like me and very likely you (given your comment). So standing the fact that I really love the lectures Prof. Boyd gives, how do you think this
Video should achieve such a large number?
AI/ML is very popular this days.
1) Maybe if append this work into title and description that I will popup this video in raitings.
2) Also EE263 L1 have been watched e.g. for th-cam.com/video/bf1264iFr-w/w-d-xo.html for 151Kilo times. So it was a reason why e.g. I hoped for video to be popular
I really wished they asked Prof Boyd more questions about neural networks.
Very Strange why this video has only 709 views, and why not 700 000.