Quantitative Analysis of Consensus Algorithms

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Robust Distributed Learning

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Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work t ...

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This paper presents an extension to PathFinder FPGA routing algorithm, which enables it to deliver FPGA designs free from risks of crosstalk attacks. Crosstalk side-channel attacks are a real threat in large designs assembled from various IPs, where some I ...

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Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

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The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

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Laser-induced densification of fused silica using spatially overlapping sub-30fs pulses

Yves Bellouard, Farhang Nabiei, Benjamin Wesley Mc Millen

Over the past several years, non-ablative femtosecond laser exposure with spatially overlapping (i.e., spatially cumulative) pulses has emerged as a key process in three-dimensional writing of patterns in bulk of dielectric substrates. When temporally non- ...

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X-Attack: Remote Activation of Satisfiability Don’t-Care Hardware Trojans on Shared FPGAs

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Albeit very appealing, FPGA multitenancy in the cloud computing environment is currently on hold due to a number of recently discovered vulnerabilities to side-channel attacks and covert communication. In this work, we successfully demonstrate a new attack ...

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The type VI secretion system (T6SS) is a nanomachine used by many bacteria to drive a toxin-laden needle into other bacterial cells. Although the potential to influence bacterial competition is clear, the fitness impacts of wielding a T6SS are not well und ...

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Analogue computing with metamaterials

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Despite their widespread use for performing advanced computational tasks, digital signal processors suffer from several restrictions, including low speed, high power consumption and complexity, caused by costly analogue-to-digital converters. For this reas ...

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Convergence without Convexity: Sampling, Optimization, and Games

Ya-Ping Hsieh

Many important problems in contemporary machine learning involve solving highly non- convex problems in sampling, optimization, or games. The absence of convexity poses significant challenges to convergence analysis of most training algorithms, and in some ...

EPFL2020