Publications associées à Théorie algorithmique de l'information

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

EPFL2024

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Jan Sickmann Hesthaven, Federico Pichi

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Academic Press Inc Elsevier Science2024

Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Ali Garjani

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

IEEE COMPUTER SOC2023

From Archival Sources to Structured Historical Information: Annotating and Exploring the "Accordi dei Garzoni"

Frédéric Kaplan, Maud Ehrmann, Orlin Biserov Topalov

If automatic document processing techniques have achieved a certain maturity for present time documents, the transformation of hand-written documents into well-represented, structured and connected data which can satisfactorily be used for historical study ...

Routledge, Taylor & Francis Group2023

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

Theory and application of a data-driven approach to compressive spectrometry in the assessment of neurophotic stimulation

Forrest Simon Webler

Recent advances in biology and neuroscience have elucidated pathways in which visible light initiates a signaling process, via the eye, responsible for activating direct and indirect biological responses. While the full impact of unnatural light patterns o ...

EPFL2022

Prompt–RSVQA: Prompting visual context to a language model for Remote Sensing Visual Question Answering

Devis Tuia, Christel Marie Tartini-Chappuis, Sylvain Lobry, Valérie Zermatten

Remote sensing visual question answering (RQA) was recently proposed with the aim of interfacing natural language and vision to ease the access of information contained in Earth Observation data for a wide audience, which is granted by simple questions in ...

2022

Online Dating Quantification Practices: A Human-Machine Learning Process

Jessica Carolina Pidoux

The phenomenon of online dating via web and mobile phone applications involves several actors: graphical interfaces, developers, algorithmic systems for user matching, and users. These actors have been studied in parallel by the social sciences and by comp ...

EPFL2021

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed for understanding how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment with a swarm of drones over a de ...

2020

Lupulus: A Flexible Hardware Accelerator For Neural Networks

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Robert Giterman, Andreas Toftegaard Kristensen

Neural networks have become indispensable for a wide range of applications, but they suffer from high computational- and memory-requirements, requiring optimizations from the algorithmic description of the network to the hardware implementation. Moreover, ...

IEEE2020

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

Babak Falsafi, Alexandros Daglis, Eva Darulova, Mattia Cacciotti, Damien Zufferey, Dorde Jevdic, Sasa Misailovic

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from cor ...

ASSOC COMPUTING MACHINERY2020

Noise-Resilient and Interpretable Epileptic Seizure Detection

David Atienza Alonso, Amir Aminifar, Anthony Hitchcock Thomas

Deep convolutional neural networks have recently emerged as a state-of-the art tool in detection of seizures. Such models offer the ability to extract complex nonlinear representations of an electroencephalogram (EEG) signal which can improve accuracy over ...

IEEE2020

On the choice of metric in gradient-based theories of brain function

Wulfram Gerstner, Johanni Michael Brea, Jean-Pascal Théodor Pfister

The idea that the brain functions so as to minimize certain costs pervades theoretical neuroscience. Because a cost function by itself does not predict how the brain finds its minima, additional assumptions about the optimization method need to be made to ...

2020

Quantification of the conditional value of SHM data for the fatigue safety evaluation of a road viaduct

Eugen Brühwiler, Imane Bayane

Fatigue safety verification of existing bridges that uses ‘‘re-calculation’’ based on codes, usually results in insufficient fatigue safety, triggering invasive interventions. Instead of “re-calculation”, Structural Health Monitoring (SHM) should be used f ...

2019

Transforming scholarship in the archives through handwritten text recognition Transkribus as a case study

Frédéric Kaplan, Sofia Ares Oliveira

Purpose An overview of the current use of handwritten text recognition (HTR) on archival manuscript material, as provided by the EU H2020 funded Transkribus platform. It explains HTR, demonstrates Transkribus, gives examples of use cases, highlights the af ...

2019

Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks

Silvestro Micera

BackgroundTo assist people with disabilities, exoskeletons must be provided with human-robot interfaces and smart algorithms capable to identify the user's movement intentions. Surface electromyographic (sEMG) signals could be suitable for this purpose, bu ...

BioMed Central2019

High-Dimensional Inference on Dense Graphs with Applications to Coding Theory and Machine Learning

Mohamad Baker Dia

We are living in the era of "Big Data", an era characterized by a voluminous amount of available data. Such amount is mainly due to the continuing advances in the computational capabilities for capturing, storing, transmitting and processing data. However, ...

EPFL2018

Probing non-Gaussian stochastic gravitational wave backgrounds with LISA

Daniel Garcia Figueroa, Nicola Bartolomei, Valerie Fiona Domcke

The stochastic gravitational wave background (SGWB) contains a wealth of information on astrophysical and cosmological processes. A major challenge of upcoming years will be to extract the information contained in this background and to disentangle the con ...

IOP PUBLISHING LTD2018

Polarization and Channel Ordering: Characterizations and Topological Structures

Rajai Nasser

Information theory is the field in which we study the fundamental limitations of communication. Shannon proved in 1948 that there exists a maximum rate, called capacity, at which we can reliably communicate information through a given channel. However, Sha ...

EPFL2017