Publications associées à Loi du χ² non centrée

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Sabine Süsstrunk, Majed El Helou, Kaan Okumus

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

2022

3PAC: A Plug-and-Play System for Distributed Power Sharing and Communication in Modular Robots

Jamie Paik, Kevin Andrew Holdcroft, Christoph Heinrich Belke

In modular robotics, there is classically a compromise between coupling complexity and functionality. The mechanical and electrical designs are linked, such that adding electrical features often requires redesigning the mechanical components. However, incr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Rachid Guerraoui, El Mahdi El Mhamdi, Sébastien Louis Alexandre Rouault

Byzantine-resilient Stochastic Gradient Descent (SGD) aims at shielding model training from Byzantine faults, be they ill-labeled training datapoints, exploited software/hardware vulnerabilities, or malicious worker nodes in a distributed setting. Two rece ...

2021

Work fluctuations in the active Ornstein-Uhlenbeck particle model

Francesco Cagnetta

We study the large deviations of the power injected by the active force for an active Ornstein-Uhlenbeck particle (AOUP), free or in a confining potential. For the free-particle case, we compute the rate function analytically in d-dimensions from a saddle- ...

IOP Publishing Ltd2021

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Marco Mattavelli, Simone Casale Brunet

Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illus ...

IEEE2021

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Daniel Kuhn, Andreas Krause, Tobias Sutter

Training models that perform well under distribution shifts is a central challenge in machine learning. In this paper, we introduce a modeling framework where, in addition to training data, we have partial structural knowledge of the shifted test distribut ...

2021

Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Applying SHARK-X to perform data assimilation with the LWR-PROTEUS Phase II integral experiments

Andreas Pautz, Mathieu Hursin, Daniel Jerôme Siefman

Data assimilation methods have recently been implemented in the sensitivity analysis and uncertainty quantification tool SHARK-X. This paper presents how they were used with sensitivity coefficients and randomly-sampled nuclear data to simulate integral pa ...

PERGAMON-ELSEVIER SCIENCE LTD2020

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Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Loi du χ² non centrée

Bringing casting to microfabrication: processing and deformation of microcastings

Making Computer Vision Models Robust and Adaptive

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

3PAC: A Plug-and-Play System for Distributed Power Sharing and Communication in Modular Robots

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Work fluctuations in the active Ornstein-Uhlenbeck particle model

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Convergence of adaptive algorithms for constrained weakly convex optimization

Applying SHARK-X to perform data assimilation with the LWR-PROTEUS Phase II integral experiments

Graph Chatbot

Chattez avec Graph Search

Bringing casting to microfabrication: processing and deformation of microcastings

Applying SHARK-X to perform data assimilation with the LWR-PROTEUS Phase II integral experiments

3PAC: A Plug-and-Play System for Distributed Power Sharing and Communication in Modular Robots

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Robust Generalization despite Distribution Shift via Minimum Discriminating Information

Convergence of adaptive algorithms for constrained weakly convex optimization

Making Computer Vision Models Robust and Adaptive

Work fluctuations in the active Ornstein-Uhlenbeck particle model

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples