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To clarify, your method assumes the input moments correspond to the traditional first k moments ie. x, x^2... x^k of a distribution, correct? What if I would like to find the maximum entropy distribution for a custom set of feature expectations?
To clarify, your method assumes the input moments correspond to the traditional first k moments ie. x, x^2... x^k of a distribution, correct? What if I would like to find the maximum entropy distribution for a custom set of feature expectations?