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Valuable Detours: Least-Cost Anypath Routing

Publications associées (30)

Efficient protocols for oblivious linear function evaluation from ring-LWE

An oblivious linear function evaluation protocol, or OLE, is a two-party protocol for the function f (x) = ax + b, where a sender inputs the field elements a, b, and a receiver inputs x and learns f (x). OLE can be used to build secret-shared multiplicatio ...

IOS PRESS2022

Hybrid Wireless-Local Communication via Information Propagation for Modular Robotic Synchronization Applications

Jamie Paik, Christoph Heinrich Belke, Kevin Andrew Holdcroft, Alexander Thomas Sigrist

Modular robots hold promise of adaptability, robustness, and versatility. Synchronization of modules is critical; if a module is asynchronous, not only will the robot fail to perform tasks properly, but its behavior may be self-destructive through self-col ...

WILEY2022

Transparent composite nano-fibre based multi-layer textile

Klaus Benedikt Schönenberger, Thierry Pelet

A composite multi-layer textile (1), comprising at least one nanofibre layer (11) with nanofibres with diameters below 100nm and one support layer (12) with microfibres with diameters below three microns, wherein the layers (11, 12) were produced by electr ...

2021

Enhancing the Reliability of Dense LoRaWAN Networks With Multi-User Receivers

Andreas Peter Burg, Joachim Tobias Tapparel, Mathieu Pierre Xhonneux

LoRaWAN is a low-power wireless technology that provides long-range connectivity to battery-powered Internet of Things (IoT) devices. To minimize the energy consumption of the IoT nodes, LoRaWAN networks use for the uplink a pure non-slotted ALOHA multiple ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Shrinking FPGA Static Power via Machine Learning-Based Power Gating and Enhanced Routing

Mirjana Stojilovic, Hossein Asadi, Zeinab Seifoori

Despite FPGAs rapidly evolving to support the requirements of the most demanding emerging applications, their high static power consumption, concentrated within the routing resources, still presents a major hurdle for low-power applications. Augmenting the ...

2021

Propagation-Loss Characterization for Livestock Implantables at (433,868,1400) MHz

Denys Nikolayev

Automated systems based on wearable sensors for livestock monitoring are becoming increasingly popular. Specifically, wireless in-body sensors could yield relevant data, such as ruminal temperature. The collection of such data requires an accurate characte ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Time-Varying Components for Enhancing Wireless Transfer of Power and Information

Romain Christophe Rémy Fleury, Mohammad Sajjad Mirmoosa, Xuchen Wang

Temporal modulation of components of electromagnetic systems provides an exceptional opportunity to engineer the response of those systems in a desired fashion, both in the time and frequency domains. For engineering time-modulated systems, one needs to th ...

American Physical Society (APS)2021

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek, Arthur Jacot

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation

Vincent Gramoli

There is an increasing interest in a fast-growing machine learning technique called Federated Learning (FL), in which the model training is distributed over mobile user equipment (UEs), exploiting UEs' local computation and training data. Despite its advan ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Private and Secure Distributed Learning

Georgios Damaskinos

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

EPFL2020

Publications associées (30)

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

Federated Learning Over Wireless Networks: Convergence Analysis and Resource Allocation

Vincent Gramoli

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Private and Secure Distributed Learning

Georgios Damaskinos

EPFL2020