Gradient descent: Difference between revisions
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Thundergnat (talk | contribs) (Re-downgrade to draft. Really, this doesn't even make it to the level of draft) |
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{{draft task|Optimization}} |
{{draft task|Optimization}} |
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Gradient descent (also known as steepest descent) is a first-order iterative optimization algorithm for finding the minimum of a function which is described in [https://en.wikipedia.org/wiki/Gradient_descent this Wikipedia article]. |
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;Task |
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Use this algorithm to search for minimum values of the bi-variate function: |
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f(x, y) = (x - 1)(x - 1)e^(-y^2) + y(y+2)e^(-2x^2) |
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around x = 0.1 and y = -1. |
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[https://books.google.co.uk/books?id=dFHvBQAAQBAJ&pg=PA543&lpg=PA543&dq=c%23+steepest+descent+method+to+find+minima+of+two+variable+function&source=bl&ots=TCyD-ts9ui&sig=ACfU3U306Og2fOhTjRv2Ms-BW00IhomoBg&hl=en&sa=X&ved=2ahUKEwitzrmL3aXjAhWwVRUIHSEYCU8Q6AEwCXoECAgQAQ#v=onepage&q=c%23%20steepest%20descent%20method%20to%20find%20minima%20of%20two%20variable%20function&f=false This book excerpt] shows sample C# code for solving this task. |
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=={{header|TypeScript}}== |
=={{header|TypeScript}}== |
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