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Open-source governance

Related publications (109)

Learning from History for Byzantine Robust Optimization

Martin Jaggi, Lie He, Sai Praneeth Reddy Karimireddy

Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Benchmarking, Analysis, and Optimization of Serverless Function Snapshots

Edouard Bugnion, Evangelos Marios Kogias, Boris Robert Grot, Dmitrii Ustiugov

Serverless computing has seen rapid adoption due to its high scalability and flexible, pay-as-you-go billing model. In serverless, developers structure their services as a collection of functions, sporadically invoked by various events like clicks. High in ...

2021

Multiparty Homomorphic Encryption from Ring-Learning-with-Errors

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat, Christian Vincent Mouchet

We propose and evaluate a secure-multiparty-computation (MPC) solution in the semi-honest model with dishonest majority that is based on multiparty homomorphic encryption (MHE). To support our solution, we introduce a multiparty version of the Brakerski-Fa ...

2021

Common workflows for computing material properties using different quantum engines

Berend Smit, Nicola Marzari, Giovanni Pizzi, Martin Uhrin, Marnik Bercx, Kristjan Eimre, Austin Jacob Zadoks, Samuel Poncé, Aliaksandr Yakutovich, Sebastiaan Philippe Huber, Conrad Johnston, Christopher John Sewell, Gian-Marco Rignanese

The prediction of material properties based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods is both a boon ...

2021

Intelligent Management of Underground Infrastructure

Mohammadhossein Esmaeelzadeh

Today, different software exists to Predict the Likelihood of Failure (LoF) for the pipes in the water networks. The LoF is used to prioritize the pipes for renovation planning of the water networks. The modern techniques use statistical and/orMachine Lear ...

2021

Faster Parallel Training of Word Embeddings

Martin Jaggi

Word embeddings have gained increasing popularity in the recent years due to the Word2vec library and its extension fastText that uses subword information. In this paper, we aim at improving the execution speed of fastText training on homogeneous multi- an ...

IEEE COMPUTER SOC2021

New Reliability Assessment of MEMS Components under Accumulative Testing for Space Applications

Maxime Auchlin

This dissertation proposes a novel accumulative test method for MEMS-based, commercial off-the-shelves inertial measure units (IMUs) from the automotive field. The need for clarification and augmentation of the corpus of knowledge on MEMS reliability for s ...

EPFL2021

Online Contention Resolution Schemes With Applications To Bayesian Selection Problems

Ola Nils Anders Svensson, Moran Feldman, Rico Zenklusen

We introduce a new rounding technique designed for online optimization problems, which is related to contention resolution schemes, a technique initially introduced in the context of submodular function maximization. Our rounding technique, which we call o ...

2021

Advances and Open Problems in Federated Learning

Martin Jaggi, Sebastian Urban Stich, Lie He, Yang Liu, Ayfer Özgür Aydin, Florian Tramèr, Qiang Yang, Ananda Theertha Suresh, Badih Ghazi

Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decen ...

NOW PUBLISHERS INC2021

Analysis of SwissCovid

Serge Vaudenay, Martin Vuagnoux

We present an analysis of the SwissCovid application which is currently being tested. We observe that the essential part of SwissCovid is under the control of Apple and Google. Outsourcing the heart of SwissCovid to Apple and Google has apparent benefits i ...

2020

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