15 citations · 37 across the 11 of their papers we have counts for
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cs.LG2020★ 5 cited
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,…
math.PR2020
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…
math-ph2020★ 4 cited
Quantum Aitchison geometry
Attila Andai, Attila Lovas
Multiplying a likelihood function with a positive number makes no difference in Bayesian statistical inference, therefore after normalization the likelihood function in many cases…