Publication

A Learning-Based Framework for Quantized Compressed Sensing

Publications associées (29)

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Rachid Guerraoui, Anne-Marie Kermarrec, Sadegh Farhadkhani, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

First detection of the BAO signal from early DESI data

Anand Stéphane Raichoor, Andrei Variu, Cheng Zhao, David Schlegel

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sam ...

Oxford Univ Press2023

The inductive bias of deep learning: Connecting weights and functions

Guillermo Ortiz Jimenez

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

EPFL2023

Center-aware Adversarial Augmentation for Single Domain Generalization

Mathieu Salzmann, Zhiye Wang

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

IEEE COMPUTER SOC2023

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

Maria del Carmen Sandi Perez, Mandy Meijer

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Modality-invariant Visual Odometry for Embodied Vision

Amir Roshan Zamir, Roman Christian Bachmann, Marius Reinhard Memmel

Effectively localizing an agent in a realistic, noisy setting is crucial for many embodied vision tasks. Visual Odometry (VO) is a practical substitute for unreliable GPS and compass sensors, especially in indoor environments. While SLAM-based methods show ...

Ieee Computer Soc2023