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Protecting Circuits From Computationally Bounded And Noisy Leakage

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Lightning strikes can seriously affect the reliability and availability of electrical infrastructures. The computation of lightning-electromagnetic fields represents one of the most crucial steps in the evaluation of the induced effects; thus, having at di ...

Elsevier2022

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We study the computational complexity of the optimal transport problem that evaluates the Wasser- stein distance between the distributions of two K-dimensional discrete random vectors. The best known algorithms for this problem run in polynomial time in th ...

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cRacklet: a spectral boundary integral method library for interfacial rupture simulation

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The study of dynamically propagating rupture along interfaces is of prime importance in various fields and system sizes, including tribology (nm to m), engineering (mm to m) and geophysics (m to km) (Armstrong-Hélouvry et al., 1994; Ben-Zion, 2008; Vanossi ...

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OXFORD UNIV PRESS2022

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AMER MATHEMATICAL SOC2021

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Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels. However, the performance of AirComp is bott ...

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Unbiased Monte Carlo cluster updates with autoregressive neural networks

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Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, used with Markov chain Monte Carlo sampling, provide good approximations to s ...

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AKSEL: Fast Byzantine SGD

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Modern machine learning architectures distinguish servers and workers. Typically, a d-dimensional model is hosted by a server and trained by n workers, using a distributed stochastic gradient descent (SGD) optimization scheme. At each SGD step, the goal is ...

Schloss Dagstuhl--Leibniz-Zentrum für Informatik2021