Zobrazeno 1 - 10
of 1 909
pro vyhledávání: '"P. Müllner"'
Autor:
Kowald, Dominik, Scher, Sebastian, Pammer-Schindler, Viktoria, Müllner, Peter, Waxnegger, Kerstin, Demelius, Lea, Fessl, Angela, Toller, Maximilian, Estrada, Inti Gabriel Mendoza, Simic, Ilija, Sabol, Vedran, Truegler, Andreas, Veas, Eduardo, Kern, Roman, Nad, Tomislav, Kopeinik, Simone
Artificial intelligence (AI) technologies (re-)shape modern life, driving innovation in a wide range of sectors. However, some AI systems have yielded unexpected or undesirable outcomes or have been used in questionable manners. As a result, there ha
Externí odkaz:
http://arxiv.org/abs/2411.09973
Autor:
Honz, Florian, Müllner, Paul, Hentschel, Michael, Nevlacsil, Stefan, Kraft, Jochen, Sagmeister, Martin, Walther, Philip, Hainberger, Rainer, Schrenk, Bernhard
We show simplified DPS-QKD using a SiN micro-ring resonator operated at 852 nm. A raw-key rate of up to 25.3 kb/s is reached at a QBER suitable for secure-key extraction. Short-reach QKD operation is maintained for zero-touch link layouts with C-band
Externí odkaz:
http://arxiv.org/abs/2411.08721
Autor:
Duricic, Tomislav, Müllner, Peter, Weidinger, Nicole, ElSayed, Neven, Kowald, Dominik, Veas, Eduardo
Many industrial sectors rely on well-trained employees that are able to operate complex machinery. In this work, we demonstrate an AI-powered immersive assistance system that supports users in performing complex tasks in industrial environments. Spec
Externí odkaz:
http://arxiv.org/abs/2407.09147
Autor:
Escobedo, Gustavo, Moscati, Marta, Muellner, Peter, Kopeinik, Simone, Kowald, Dominik, Lex, Elisabeth, Schedl, Markus
Users' interaction or preference data used in recommender systems carry the risk of unintentionally revealing users' private attributes (e.g., gender or race). This risk becomes particularly concerning when the training data contains user preferences
Externí odkaz:
http://arxiv.org/abs/2406.11505
Collaborative filtering-based recommender systems leverage vast amounts of behavioral user data, which poses severe privacy risks. Thus, often, random noise is added to the data to ensure Differential Privacy (DP). However, to date, it is not well un
Externí odkaz:
http://arxiv.org/abs/2401.03883
Autor:
Konieczny, Jakub, Müllner, Clemens
We fully classify automatic sequences $a$ over a finite alphabet $\Omega$ with the property that each word over $\Omega$ appears is $a$ along an arithmetic progression. Using the terminology introduced by Avgustinovich, Fon-Der-Flaass and Frid, these
Externí odkaz:
http://arxiv.org/abs/2309.03180
We show that computing the strongest polynomial invariant for single-path loops with polynomial assignments is at least as hard as the Skolem problem, a famous problem whose decidability has been open for almost a century. While the strongest polynom
Externí odkaz:
http://arxiv.org/abs/2307.10902
We present an exact approach to analyze and quantify the sensitivity of higher moments of probabilistic loops with symbolic parameters, polynomial arithmetic and potentially uncountable state spaces. Our approach integrates methods from symbolic comp
Externí odkaz:
http://arxiv.org/abs/2305.15259
Autor:
Vojtěch Müllner, Kamil Nečas
Publikováno v:
Vojenské rozhledy, Vol 33, Iss 3, Pp 3-26 (2024)
An important part of NATO's deterrence and defence role is its military presence in the eastern part of the Alliance's territory, represented by the Bucharest Nine (B9). The ability of this group to fulfil its strategic mission depends on the conditi
Externí odkaz:
https://doaj.org/article/102865d8fc36478a994dbc97ae9517d2
Autor:
Konieczny, Jakub, Müllner, Clemens
Publikováno v:
Ergod. Th. Dynam. Sys. 44 (2024) 2621-2648
We study bracket words, which are a far-reaching generalisation of Sturmian words, along Hardy field sequences, which are a far-reaching generalisation of Piatetski--Shapiro sequences $\lfloor n^c \rfloor$. We show that thus obtained sequences are de
Externí odkaz:
http://arxiv.org/abs/2302.09626