no code implementations • 1 Mar 2023 • Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch, Srikanth Kandula, Ishai Menache, Michael Schapira, Aviv Tamar
Routing is, arguably, the most fundamental task in computer networking, and the most extensively studied one.
no code implementations • 11 Feb 2023 • Guy Amir, Osher Maayan, Tom Zelazny, Guy Katz, Michael Schapira
Deep neural networks (DNNs) are the workhorses of deep learning, which constitutes the state of the art in numerous application domains.
no code implementations • 8 Feb 2022 • Guy Amir, Tom Zelazny, Guy Katz, Michael Schapira
Deep neural networks (DNNs) have become the technology of choice for realizing a variety of complex tasks.
1 code implementation • 25 May 2021 • Guy Amir, Michael Schapira, Guy Katz
Deep neural networks (DNNs) have gained significant popularity in recent years, becoming the state of the art in a variety of domains.
no code implementations • 7 Oct 2020 • Noga H. Rotman, Michael Schapira, Aviv Tamar
We illustrate the usefulness of online safety assurance in the context of the proposed deep reinforcement learning (RL) approach to video streaming.
no code implementations • 10 Aug 2017 • Asaf Valadarsky, Michael Schapira, Dafna Shahaf, Aviv Tamar
Can ideas and techniques from machine learning be leveraged to automatically generate "good" routing configurations?
1 code implementation • 19 May 2015 • Rishab Nithyanand, Oleksii Starov, Adva Zair, Phillipa Gill, Michael Schapira
We find that up to 40% of all circuits created by Tor are vulnerable to attacks by traffic correlation from Autonomous System (AS)-level adversaries, 42% from colluding AS-level adversaries, and 85% from state-level adversaries.
Cryptography and Security