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Distributed Sensing of Signals under a Sparse Filtering Model

Publications associées (29)

The inductive bias of deep learning: Connecting weights and functions

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

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

A study of the K^(+) → π^(0)e^(+)νγ decay

Alessandro Mapelli, Radoslav Marchevski, Alina Kleimenova

A sample of 1.3 x 10^(5) K^(+) → π^(0)e^(+)νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinemati ...

Springer Nature2023

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

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

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

Jürg Alexander Schiffmann, Cyril Picard, Faez Ahmed

Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

Amer Soc Mechanical Engineers2023

How to Boost Face Recognition with StyleGAN?

Nikita Durasov

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

Ieee Computer Soc2023

Preserved Corticospinal Tract Revealed by Acute Perfusion Imaging Relates to Better Outcome After Thrombectomy in Stroke

Friedhelm Christoph Hummel, Philipp Johannes Koch

BACKGROUND:The indication for mechanical thrombectomy (MT) in stroke patients with large vessel occlusion has been constantly expanded over the past years. Despite remarkable treatment effects at the group level in clinical trials, many patients remain sev ...

Lippincott Williams & Wilkins2023