Zobrazeno 1 - 10
of 256
pro vyhledávání: '"Urbanke R"'
Autor:
Nadlinger, D. P., Drmota, P., Nichol, B. C., Araneda, G., Main, D., Srinivas, R., Lucas, D. M., Ballance, C. J., Ivanov, K., Tan, E. Y-Z., Sekatski, P., Urbanke, R. L., Renner, R., Sangouard, N., Bancal, J-D.
Publikováno v:
Nature 607, 682-686 (2022)
Cryptographic key exchange protocols traditionally rely on computational conjectures such as the hardness of prime factorisation to provide security against eavesdropping attacks. Remarkably, quantum key distribution protocols like the one proposed b
Externí odkaz:
http://arxiv.org/abs/2109.14600
We present two sequences of ensembles of non-systematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit.
Externí odkaz:
http://arxiv.org/abs/cs/0409027
Publikováno v:
IEEE Transactions on Information Theory, Vol. 51 (7), pp. 2352-2379, July 2005
We present two sequences of ensembles of non-systematic irregular repeat-accumulate codes which asymptotically (as their block length tends to infinity) achieve capacity on the binary erasure channel (BEC) with bounded complexity per information bit.
Externí odkaz:
http://arxiv.org/abs/cs/0409026
Akademický článek
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Autor:
G��uch, Grzegorz, Urbanke, R��diger
Symmetries have proven to be important ingredients in the analysis of neural networks. So far their use has mostly been implicit or seemingly coincidental. We undertake a systematic study of the role that symmetry plays. In particular, we clarify how
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::459faa724fa781d699938e41cc34ab0e
http://arxiv.org/abs/2104.05508
http://arxiv.org/abs/2104.05508
Autor:
G��uch, Grzegorz, Urbanke, R��diger
We prove an exponential separation for the sample complexity between the standard PAC-learning model and a version of the Equivalence-Query-learning model. We then show that this separation has interesting implications for adversarial robustness. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1da0fbb0381feb2814a580d5666e1709
http://arxiv.org/abs/2102.05475
http://arxiv.org/abs/2102.05475
Autor:
Ivanov, Kirill, Urbanke, R��diger L.
Recently it was proved that if a linear code is invariant under the action of a doubly transitive permutation group, it achieves the capacity of erasure channel. Therefore, it is of sufficient interest to classify all codes, invariant under such perm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::146c45e92fa663637bbf15f079b6f6dd
http://arxiv.org/abs/2010.15453
http://arxiv.org/abs/2010.15453
Autor:
G��uch, Grzegorz, Urbanke, R��diger
Modern machine learning models with very high accuracy have been shown to be vulnerable to small, adversarially chosen perturbations of the input. Given black-box access to a high-accuracy classifier $f$, we show how to construct a new classifier $g$
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb9e2be310b67a06304c30c529d32f95
http://arxiv.org/abs/1912.07561
http://arxiv.org/abs/1912.07561
Autor:
K. P. Maier, Hubert E. Blum, Urbanke R, Friedrich Deinhardt, R. Lesch, Kluge F, Wolfgang Gerok, Berthold H, G. G. Frösner, H. Haas
Publikováno v:
DMW - Deutsche Medizinische Wochenschrift. 105:1179-1183
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::699bb33df0c15f3f4c06afecf134f42c
https://doi.org/10.1055/s-2008-1070835
https://doi.org/10.1055/s-2008-1070835
We show that Reed-Muller codes achieve capacity under maximum a posteriori bit decoding for transmission over the binary erasure channel for all rates $0 < R < 1$. The proof is generic and applies to other codes with sufficient amount of symmetry as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0902a246a52d073d2e79fdd29e0a0385
http://arxiv.org/abs/1505.05831
http://arxiv.org/abs/1505.05831