2 citations · 2 across the 2 of their papers we have counts for
8 papers
On the stability of the stochastic gradient Langevin algorithm with dependent data stream
Miklós Rásonyi, Kinga Tikosi
We prove, under mild conditions, that the stochastic gradient Langevin dynamics converges to a limiting law as time tends to infinity, even in the case where the driving data seque…
Optimal long-term investment in illiquid markets when prices have negative memory
Miklós Rásonyi, Lóránt Nagy
In a discrete-time financial market model with instantaneous price impact, we find an asymptotically optimal strategy for an investor maximizing her expected wealth. The asset pric…
Ergodic theorems for queuing systems with dependent inter-arrival times
Attila Lovas, Miklós Rásonyi
We study a G/GI/1 single-server queuing model with i.i.d.\ service times that are independent of a stationary process of inter-arrival times. We show that the distribution of the w…
Markov chains in random environment with applications in queueing theory and machine learning
Attila Lovas, Miklós Rásonyi
We prove the existence of limiting distributions for a large class of Markov chains on a general state space in a random environment. We assume suitable versions of the standard dr…
Learning Threshold-Type Investment Strategies with Stochastic Gradient Method
Zsolt Nika, Miklós Rásonyi
In online portfolio optimization the investor makes decisions based on new, continuously incoming information on financial assets (typically their prices). In our study we consider…
On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case
Ngoc Huy Chau, Éric Moulines, Miklos Rásonyi +2
We consider the problem of sampling from a target distribution, which is \emph {not necessarily logconcave}, in the context of empirical risk minimization and stochastic optimizati…