25 citations · 48 across the 13 of their papers we have counts for
4 papers · 1 filter
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
Attila Lovas, Iosif Lytras, Miklós Rásonyi +1
Artificial neural networks (ANNs) are typically highly nonlinear systems which are finely tuned via the optimization of their associated, non-convex loss functions. In many cases,…
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…
Invariant measures for multidimensional fractional stochastic volatility models
Balázs Gerencsér, Miklós Rásonyi
We establish convergence to an invariant measure as time tends to infinity, for a large class of (possibly non-Markovian) stochastic volatility models. Our arguments are based on a…