Publications associées à A Data-Driven Approach Based on Multivariate Copulas for Quantitative Risk Assessment of Concrete Dam

Extensions of Peer Prediction Incentive Mechanisms

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Shear and steel-fibre reinforcement for the punching resistance of flat slabs at internal and edge columns

Diego Hernández Fraile

Reinforced concrete flat slabs consist of a continuous, thin concrete plate that rests on a grid of columns. The supporting surface of the columns is very small compared to the floor plan dimensions, leading to concentrations of shear forces near the colum ...

EPFL2024

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Daniel Kressner, Haoze He

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Siam Publications2024

On the Generalization of Stochastic Gradient Descent with Momentum

Volkan Cevher, Kimon Antonakopoulos

While momentum-based accelerated variants of stochastic gradient descent (SGD) are widely used when training machine learning models, there is little theoretical understanding on the generalization error of such methods. In this work, we first show that th ...

Microtome Publishing2024

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Yanina Yurina Shkel

Given two jointly distributed random variables (X,Y), a functional representation of X is a random variable Z independent of Y, and a deterministic function g(⋅,⋅) such that X=g(Y,Z). The problem of finding a minimum entropy functional representation is kn ...

2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

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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

Sensitivity to user mischaracterizations in electric vehicle charging

Nils Gustav Nilsson

In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...

ELSEVIER2023

Safety climate in university laboratories. Part I: model development and practical application

Thierry Meyer, Anastasia Jung

Safety climate assessment has become a regular practice for most organisations. However, it is often limited to questionnaires, providing only qualitative information. The indicator-based approach takes precedence over decision-making, and practical risk a ...

2023

Combining European and US risk prediction models with polygenic risk scores to refine cardiovascular prevention: the CoLaus|PsyCoLaus Study

Stéphane Fournier, Roxane De La Harpe, Jacques Fellay, Christian Axel Wandall Thorball

Lay Summary The aim of this study is to determine whether using polygenic risk scores improves the prediction of atherosclerotic cardiovascular disease risk when combined with clinical scores currently recommended by European and US guidelines on cardiovas ...

OXFORD UNIV PRESS2023

Safety risk management in University laboratories

Anastasia Jung

Risk management has become an essential element in the functioning of modern society. Correct risk identification and assessment are undoubtedly crucial to improving overall safety; nevertheless, often, it is accompanied by the wrong selection of correctiv ...

EPFL2023

Robust optimization of control parameters for WEC arrays using stochastic methods

Edie Miglio, Tommaso Vanzan

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

Journal of Computational Physics2023

CONVERGENCE AND NONCONVERGENCE OF SCALED SELF-INTERACTING RANDOM WALKS TO BROWNIAN MOTION PERTURBED AT EXTREMA

Thomas Mountford

We use generalized Ray-Knight theorems, introduced by B. Toth in 1996, together with techniques developed for excited random walks as main tools for establishing positive and negative results concerning convergence of some classes of diffusively scaled sel ...

Inst Mathematical Statistics-Ims2023

The importance of young professionals for dam engineering in Switzerland

Valentina Favero, Samuel Luke Vorlet

In Switzerland, hydropower is the main energy source and contributes to about 58.3% of the total production. The 2050 energy strategy aims to increase this share in the coming decades. This increase is a challenge for hydropower plants. The maintenance and ...

CRC Press/Balkema2023

Can one hear the shape of a target zone?

Max-Olivier Hongler

We develop an exchange rate target zone model with finite exit time and non-Gaussian tails. We show how the tails are a consequence of time-varying investor risk aversion, which generates mean-preserving spreads in the fundamental distribution. We solve ex ...

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Spatial Distributions of Diarrheal Cases in Relation to Housing Conditions in Informal Settlements: A Cross-Sectional Study in Abidjan, Côte d’Ivoire

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In addition to individual practices and access to water, sanitation, and hygiene (WASH) facilities, housing conditions may also be associated with the risk of diarrhea. Our study embraced a broad approach to health determinants by looking at housing depriv ...

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Bed Topography Inference from Velocity Field Using Deep Learning

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Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...

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Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Prateek Bansal, Thomas Gasos

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

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Automated Design Appraisal: Estimating Real Estate Price Growth and Value at Risk Due to Local Development

Adam Robert Swietek

Financial criteria in architectural design evaluation are limited to cost performance. Here, I introduce a method – Automated Design Appraisal (ADA) – to predict the market price of a generated building design concept within a local urban context. Integrat ...

2023