Publications related to Online machine learning

The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic

Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. The COUGHVID dataset provide ...

2021

21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

Devis Tuia, Benjamin Alexander Kellenberger

We address the task of automatically detecting and counting seabirds in unmanned aerial vehicle (UAV) imagery using deep convolutional neural networks (CNNs). Our study area, the coast of West Africa, harbours significant breeding colonies of terns and gul ...

2021

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

Subspace-Based Learning for Automatic Dysarthric Speech Detection

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

To assist the clinical diagnosis and treatment of speech dysarthria, automatic dysarthric speech detection techniques providing reliable and cost-effective assessment are indispensable. Based on clinical evidence on spectro-temporal distortions associated ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Wasserstein Adversarial Regularization for learning with label noise

Devis Tuia, Sylvain Lobry, Nicolas Courty

Noisy labels often occur in vision datasets, especially when they are obtained from crowdsourcing or Web scraping. We propose a new regularization method, which enables learning robust classifiers in presence of noisy data. To achieve this goal, we propose ...

2021

Adaptive Social Learning

Ali H. Sayed, Virginia Bordignon

This work proposes a novel strategy for social learning by introducing the critical feature of adaptation. In social learning, several distributed agents update continually their belief about a phenomenon of interest through: i) direct observation of strea ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Aude Billard, Sthithpragya Gupta, Walid Amanhoud, Farshad Khadivar

The inverse dynamics of a robotic manipulator is instrumental in precise robot control and manipulation. However, acquiring such a model is challenging, not only due to unmodelled non-linearities such as joint friction, but also from a machine learning per ...

IEEE2021

Parametrized classifiers for optimal EFT sensitivity

Andrea Wulzer, Alfredo Glioti, Siyu Chen

We study unbinned multivariate analysis techniques, based on Statistical Learning, for indirect new physics searches at the LHC in the Effective Field Theory framework. We focus in particular on high-energy ZW production with fully leptonic decays, modeled ...

SPRINGER2021

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Online machine learning

The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

AKSEL: Fast Byzantine SGD

Subspace-Based Learning for Automatic Dysarthric Speech Detection

Wasserstein Adversarial Regularization for learning with label noise

Adaptive Social Learning

Analytical and Machine Learning Methods for the Complete Safe Coordination of Astrobot Swarms

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Loss landscape and symmetries in Neural Networks

Parametrized classifiers for optimal EFT sensitivity

Graph Chatbot

Chat with Graph Search

The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning

AKSEL: Fast Byzantine SGD

Parametrized classifiers for optimal EFT sensitivity

Efficient Configuration Exploration in Inverse Dynamics Acquisition of Robotic Manipulators

Adaptive Social Learning

Loss landscape and symmetries in Neural Networks

Analytical and Machine Learning Methods for the Complete Safe Coordination of Astrobot Swarms

Subspace-Based Learning for Automatic Dysarthric Speech Detection

Wasserstein Adversarial Regularization for learning with label noise