Almost sure convergence of stochastic gradient processes with matrix step sizes
Résumé
We consider a stochastic gradient process, which is a special case of stochastic approximation process, where the positive real step size a_{n} is replaced by a random matrix A_{n}: X_{n+1}=X_{n}-A_{n}∇g(X_{n})-A_{n}V_{n}. We give two theorems of almost sure convergence in the case where the equation ∇g=0 has a set of solutions.
Domaines
Statistiques [math.ST]
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