Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Maximilian Schädler"'
Autor:
Alonso Viladomat Jasso, Ark Modi, Roberto Ferrara, Christian Deppe, Janis Nötzel, Fred Fung, Maximilian Schädler
Publikováno v:
Entropy, Vol 25, Iss 9, p 1361 (2023)
Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the class
Externí odkaz:
https://doaj.org/article/9d708e8cd53d4586aa3aadfd32818a94
Autor:
Alonso Viladomat Jasso, Ark Kumar Modi, Roberto Ferrara, Janis Noetzel, Christian Deppe, Maximilian Schädler, Fred Fung
Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical fibre communication systems. Quantum nearest-neighbour clustering promises a speed-up over
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a636bf09bd1f354a3ff25fcc1dec981
https://doi.org/10.20944/preprints202305.0051.v1
https://doi.org/10.20944/preprints202305.0051.v1
Autor:
Amro Eldebiky, Georg Böcherer, Maximilian Schädler, Stefano Calabrò, Bing Li, Ulf Schlichtmann
Publikováno v:
Optical Fiber Communication Conference (OFC) 2023.
Analog in-memory computing reduces power consumption sacrificing computational accuracy. We implement multiplication-accumulation in resistive RAM accounting for non-idealities (variations, quantization, ADC noise). The floating-point performance is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc78123808c516685ea8f5df6c10bcdc
https://doi.org/10.1364/ofc.2023.m1f.3
https://doi.org/10.1364/ofc.2023.m1f.3