I have a floating point number
[1, 500] that generates a binary
y of 1 at some probability
p. And I'm trying to find the
x that has highest
p. I'm assuming there's only one maximum.
I know we can do this with simulated annealing but I don't think I should hard code temperature because I need to use the same algorithm when
x could be from
[1, 3000] or the
p distribution is little bit different.
Is there an algorithm that can converge fast to the
x with highest
p while making sure it doesn't jump around too much after it's achieved for e.x. within 0.1% of the optimal x? Specifically, it would be great if it stabilizes when near < 0.1% of optimal