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pro vyhledávání: '"Ruess A"'
Autor:
Ruess, Harald
We argue that relative importance and its equitable attribution in terms of Shapley-Owen effects is an appropriate one, and, if we accept a small number of reasonable imperatives for equitable attribution, the only way to measure fairness. On the oth
Externí odkaz:
http://arxiv.org/abs/2409.19318
Autor:
Ye, Xin, Ruess, Harald
Our main result is a polynomial time algorithm for deciding realizability for the GXU sublogic of linear temporal logic. This logic is particularly suitable for the specification of embedded control systems, and it is more expressive than GR(1). Reac
Externí odkaz:
http://arxiv.org/abs/2404.17834
The deployment of generative AI (GenAI) models raises significant fairness concerns, addressed in this paper through novel characterization and enforcement techniques specific to GenAI. Unlike standard AI performing specific tasks, GenAI's broad func
Externí odkaz:
http://arxiv.org/abs/2404.16663
Autor:
Ruess, Harald
The main result is a doubly exponential decision procedure for the first-order equality theory of streams with both arithmetic and control-oriented stream operations. This stream logic is expressive for elementary problems of stream calculus.
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Externí odkaz:
http://arxiv.org/abs/2401.02239
Autor:
Ruess, Harald
We study solutions to systems of stream inclusions of the form 'f in T(f)', where the nondeterministic transformer 'T' on omega-infinite streams is assumed to be causal in the sense that elements in output streams are determined by a finite prefix of
Externí odkaz:
http://arxiv.org/abs/2401.00164
Covariate shift may impact the operational safety performance of neural networks. A re-evaluation of the safety performance, however, requires collecting new operational data and creating corresponding ground truth labels, which often is not possible
Externí odkaz:
http://arxiv.org/abs/2307.12716
Out-of-distribution (OoD) detection techniques are instrumental for safety-related neural networks. We are arguing, however, that current performance-oriented OoD detection techniques geared towards matching metrics such as expected calibration error
Externí odkaz:
http://arxiv.org/abs/2306.08447
Publikováno v:
Brain Stimulation, Vol 17, Iss 5, Pp 1145-1154 (2024)
Background: As clinical trials involving implantable neural devices (INDs) increase in frequency and attract greater public attention, it is paramount to ensure they are conducted in alignment with fundamental ethical guidelines. Particular focus mus
Externí odkaz:
https://doaj.org/article/e3f3562c99ab45928b6d43f0d8b0a676
Autor:
Markus Eichner, Alexandra Hellerbach, Mauritius Hoevels, Klaus Luyken, Michael Judge, Daniel Rueß, Maximilian Ruge, Martin Kocher, Stefan Hunsche, Harald Treuer
Publikováno v:
Zeitschrift für Medizinische Physik, Vol 34, Iss 3, Pp 428-435 (2024)
Purpose: In robotic stereotactic radiosurgery (SRS), optimal selection of collimators from a set of fixed cones must be determined manually by trial and error. A unique and uniformly scaled metric to characterize plan quality could help identify Pare
Externí odkaz:
https://doaj.org/article/dd0e5ecf30d442afa9b48026c99a420e
Autor:
Ruess, Harald, Shankar, Natarajan
Cyberlogic is an enabling logical foundation for building and analyzing digital transactions that involve the exchange of digital forms of evidence. It is based on an extension of (first-order) intuitionistic predicate logic with an attestation and a
Externí odkaz:
http://arxiv.org/abs/2304.00060