Publication

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models

Publications associées (32)

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

EPFL2023

Active Wire Fences for Multitenant FPGAs

Mirjana Stojilovic, Ognjen Glamocanin, Andela Kostic, Stasa Kostic

When spatially shared among multiple tenants, field-programmable gate arrays (FPGAs) are vulnerable to remote power side-channel analysis attacks. Using carefully crafted on-chip voltage sensors, adversaries can extract secrets (e.g., encryption keys or th ...

2023

Federated Linear Bandit Learning via Over-the-air Computation

Xin Liu, Ting Wang, Yuning Jiang

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...

IEEE2023

Housing, street and health: a new systemic research framework

Stéphane Joost, Paola Viganò, Catarina Wall Gago, Anna Pagani, Derek Pierre Christie, Dusan Licina, Valentin Daniel Maurice Bourdon, Idris Guessous, Mathias Lerch

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

2023

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Trung-Dung Hoang, Thanh Trung Huynh

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

ELSEVIER2023

Optimizing Data Processing for Nanodiamond Based Relaxometry

Mayeul Sylvain Chipaux

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

WILEY2023

Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Emilio Maddalena

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

EPFL2023

Scalable and Privacy-Preserving Federated Principal Component Analysis

Jean-Pierre Hubaux, Jean-Philippe Léonard Bossuat, David Jules Froelicher, Joao André Gomes de Sá e Sousa, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Performance investigation of cameras using HDR sensors for daylight glare evaluations

Jan Wienold, Geraldine Cai Ting Quek, Dong Hyun Kim

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

International Commission on Illumination2023

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Alexandra Shelest

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

IOP Publishing Ltd2022

Analytical prediction of the final error due to noise in a ϕ-OTDR system

Luc Thévenaz, Li Zhang, Malak Mohamed Hossameldeen Omar Mohamed Galal, Suneetha Sebastian, Yuting Yang

An analytical expression to estimate the uncertainty on the frequency shift in ϕ-OTDR systems is established and confirmed by actual data. ...

Optica Publishing Group2022

A Cryo-CMOS Oscillator With an Automatic Common-Mode Resonance Calibration for Quantum Computing Applications

Edoardo Charbon, Fabio Sebastiano, Yue Chen

This article presents a 4-to-5 GHz LC oscillator operating at 4.2K for quantum computing applications. The phase noise (PN) specification of the oscillator is derived based on the control fidelity for a single-qubit operation. To reveal the substantial gap ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022