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pro vyhledávání: '"Kushilevitz, Eyal"'
Autor:
Wagh, Sameer, Tople, Shruti, Benhamouda, Fabrice, Kushilevitz, Eyal, Mittal, Prateek, Rabin, Tal
We propose Falcon, an end-to-end 3-party protocol for efficient private training and inference of large machine learning models. Falcon presents four main advantages - (i) It is highly expressive with support for high capacity networks such as VGG16
Externí odkaz:
http://arxiv.org/abs/2004.02229
Autor:
Kushilevitz, Eyal, Mour, Tamer
Oblivious RAM (ORAM) is a cryptographic primitive that allows a client to securely execute RAM programs over data that is stored in an untrusted server. Distributed Oblivious RAM is a variant of ORAM, where the data is stored in $m>1$ servers. Extens
Externí odkaz:
http://arxiv.org/abs/1802.05145
Autor:
Aharoni, Eldar, Kushilevitz, Eyal
We study the direct-sum problem for $k$-party ``Number On the Forehead'' (NOF) deterministic communication complexity. We prove several positive results, showing that the complexity of computing a function $f$ in this model, on $\ell$ instances, may
Externí odkaz:
http://arxiv.org/abs/1402.5311
Publikováno v:
Theoretical Computer Science 412(24), 2611-2622, 2011
Consider the "Number in Hand" multiparty communication complexity model, where k players holding inputs x_1,...,x_k in {0,1}^n communicate to compute the value f(x_1,...,x_k) of a function f known to all of them. The main lower bound technique for th
Externí odkaz:
http://arxiv.org/abs/0909.5684
Publikováno v:
In Theoretical Computer Science 2011 412(24):2611-2622
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Publikováno v:
In Theoretical Computer Science 5 September 2003 306(1-3):69-84