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Over-the-Air Computation via Reconfigurable Intelligent Surface

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Homothetic Tube Model Predictive Control With Multi-Step Predictors

Giancarlo Ferrari Trecate, Danilo Saccani, Melanie Nicole Zeilinger

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

Piscataway2023

Static Worst-Case Resource Analysis for Substrate Pallets

Simon Nicolas Perriard

We present saft, the first attempt of a static analyzer that extracts the asymptotic function complexity for the Polkadot/Substrate ecosystem, where the burden of accounting for computation resource consumption is put on the developer. saft is a tool meant ...

2023

Latency Interfaces for Systems Code

Rishabh Ramesh Iyer

This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects.Sem ...

EPFL2023

Three-dimensional inspection of nanostructures such as integrated circuits is important for security and reliability assurance. Two scanning operations are required: ptychographic to recover the complex transmissivity of the specimen, and rotation of the s ...

2023

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Wearable IoT devices and novel continuous monitoring algorithms are essential components of the healthcare transition from reactive interventions focused on symptom treatment to more proactive prevention, from one-size-fits-all to personalized medicine, an ...

IEEE2022

Privacy-Preserving Federated Analytics using Multiparty Homomorphic Encryption

David Jules Froelicher

Analyzing and processing data that are siloed and dispersed among multiple distrustful stakeholders is difficult and can even become impossible when the data are sensitive or confidential. Current data-protection and privacy regulations highly restrict the ...

EPFL2021

AKSEL: Fast Byzantine SGD

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Sébastien Louis Alexandre Rouault

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 f{\"u}r Informatik2021

Iterative distributed fault detection and isolation for linear systems based on moving horizon estimation

René Uwe Schneider, Marcello Farina

In modern engineering systems, reliability and safety can be conferred by efficient automatic monitoring and fault detection algorithms, allowing for the early identification and isolation of incipient faults. In case of large-scale and complex systems, sc ...

2020

This work presents a novel methodology for speeding up the assembly of stiffness matrices for laminate composite 3D structures in the context of isogeometric and finite element discretizations. By splitting the involved terms into their in-plane and out-of ...

2020

Roundtable Panel Discussion at DAC 2019: Evolutionary Computing or Heuristic Forever?

Giovanni De Micheli, Massimiliano Di Ventra

As demands for computing have been continuously increasing, various solutions have been proposed. Some approaches deal with improving algorithms and software programs, mainly through the tuning of advanced heuristics and learning methods. Some other tackle ...

2020