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I'm trying to get this method working. I cannot understand the computations included in the answers.

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I know what $B$ and $N$ are and how they are calculated. Can't see where the basis comes from and if it's actually given. I don't even see where it's used.

Furthermore, I can't see where $(6 \ 0)$ and $(3 \ 0)$ comes from. I subbed in the starting point into the gradient matrix and got $(3 \ 6 \ 0 \ 0)$.

Then there is also this $D_N$ which I wasn't able to get to.

I tried looking up stuff online and nothing really useful was found. The notes were extremely ambiguous and messy as well.

Any help is appreciated! Thanks.

Hypergeometry
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  • I am not sure what you are doing here, but it doesn't look like the projected gradient method. Your problem is to minimize some quadratic objective subject to two linear constraints. Your algorithm should take a descent step (as in the gradient method) followed by projection of that point onto the linear constraints. – cheyp Nov 03 '18 at 21:30
  • These are the answers to a "reduced gradient method" exercise provided by the lecturer. I'll try to make more sense of the algorithm provided. – Hypergeometry Nov 04 '18 at 06:49

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