Holonomic Gradient Descent and its Application to Fisher-Bingham Integral


The gradient descent is a general method to find a local minimum of a smooth function f(z1, . . . , zd). The method utilizes the observation that f(p) decreases if one goes from a point z = p to a “nice” direction, which is usually −(∇f)(p). As textbooks on optimizations present (see, e.g., [5], [16]), we have a lot of achievements on this method and its… (More)

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