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On the strong stability of ergodic iterations
László Györfi, Attila Lovas, Miklós Rásonyi
We revisit processes generated by iterated random functions driven by a stationary and ergodic sequence. Such a process is called strongly stable if a random initialization exists,…
Functional Central Limit Theorem and Strong Law of Large Numbers for Stochastic Gradient Langevin Dynamics
Attila Lovas, Miklós Rásonyi
We study the mixing properties of an important optimization algorithm of machine learning: the stochastic gradient Langevin dynamics (SGLD) with a fixed step size. The data stream…
Ergodic aspects of trading with threshold strategies
Attila Lovas, Miklós Rásonyi
To profit from price oscillations, investors frequently use threshold-type strategies where changes in the portfolio position are triggered by some indicators reaching prescribed l…
Stochastic Approximation in a Markovian Framework Revisited: Lipschitz Continuity of the Poisson Equation
Algo Carè, Balázs Csanád Csáji, Balázs Gerencsér +2
In this paper we revisit a fundamental technical issue within the theory of stochastic approximation (SA) in a Markovian framework, first proposed in the book by Djereveckii and Fr…