wow 9 years ago! This is still one of the first algorithm we see when learning linear programming. You guys did such a great job explaining just like the conventional way good professors teach, truly deserves more likes. Before this I've seen so many other videos but understood in this one in one go
13:36 - This question is the original question that has plagued me!! I really don't appreciate being expected to execute an algorithm (by hand?!) when what each step is actually doing has not been sufficiently explained! Fantastic lecture - where is more material?! Edit: found great material at www2.isye.gatech.edu/~sahmed/isye3133b/simplex , best I have found so far on this subject. Sign of a young / specialized subfield is that most introductory explanations are pretty bad.
I do not understand anything , how can i answer this question: You seek a local minima of a function f(x), x=(x_1,x_2) using Nelder-Meads method. You have arrived at a simplex with vertices at (1.2,0.8), (-0.4,0.6) and (0.2,1.0) with corresponding function values 2.3, 1.7 and 1.9 respectively. What will be the vertices of the next simplex? How is the point x_0 defined in case of a Nelder-Mead search in three space dimensions?
Hi Mark. Thank you. This video is really good. At 2.45 you said "It may not be obvious from that equation but since you have already seen this in the reading" what reading are you talking about ?. Are there any previous videos ?. If yes, can you please post the link. I am still not able to understand the slack variable (y1,y2) concept and how the line corresponds to y1=0 and y2=0
I do not understand anything , how can i answer this question: You seek a local minima of a function f(x), x=(x_1,x_2) using Nelder-Meads method. You have arrived at a simplex with vertices at (1.2,0.8), (-0.4,0.6) and (0.2,1.0) with corresponding function values 2.3, 1.7 and 1.9 respectively. What will be the vertices of the next simplex? How is the point x_0 defined in case of a Nelder-Mead search in three space dimensions?
wow 9 years ago! This is still one of the first algorithm we see when learning linear programming. You guys did such a great job explaining just like the conventional way good professors teach, truly deserves more likes. Before this I've seen so many other videos but understood in this one in one go
Best explanation of UA-cam
Amazing explanation sir
Great! I got what I needed! Thanks Mr Mark a lot.
13:36 - This question is the original question that has plagued me!! I really don't appreciate being expected to execute an algorithm (by hand?!) when what each step is actually doing has not been sufficiently explained! Fantastic lecture - where is more material?! Edit: found great material at www2.isye.gatech.edu/~sahmed/isye3133b/simplex , best I have found so far on this subject. Sign of a young / specialized subfield is that most introductory explanations are pretty bad.
Its a new line of approach for me with regards to simplex method, thanks a lot for sharing it with us!
This was so so well explained, it was beautiful. Thank you so much for this!
this was really beautiful . i fell in love
I do not understand anything , how can i answer this question: You seek a local minima of a function f(x), x=(x_1,x_2) using Nelder-Meads method. You have arrived at a simplex with vertices at (1.2,0.8), (-0.4,0.6) and (0.2,1.0) with corresponding function values 2.3, 1.7 and 1.9 respectively. What will be the vertices of the next simplex? How is the point x_0 defined in case of a Nelder-Mead search in three space dimensions?
So well explained, thanks.
Amazing!
Thank you. Very helpful.
thanks guys and I enjoy the way you explain it.
Awesome explanation!
You explained really well. Thank you.
fuck yes i love this guy's intuition and explanation style!!
thank u very much
Hi Mark. Thank you. This video is really good. At 2.45 you said "It may not be obvious from that equation but since you have already seen this in the reading" what reading are you talking about ?. Are there any previous videos ?. If yes, can you please post the link. I am still not able to understand the slack variable (y1,y2) concept and how the line corresponds to y1=0 and y2=0
Quite good explanation, thank you !
great explanation. Thanks a lot.
It was going good but suddenly I realized that the video is complete
I do not understand anything , how can i answer this question: You seek a local minima of a function f(x), x=(x_1,x_2) using Nelder-Meads method. You have arrived at a simplex with vertices at (1.2,0.8), (-0.4,0.6) and (0.2,1.0) with corresponding function values 2.3, 1.7 and 1.9 respectively. What will be the vertices of the next simplex? How is the point x_0 defined in case of a Nelder-Mead search in three space dimensions?
Verry much
سبحان الله وبحمده، سبحان الله العظيم.
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