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Publications associées (19)

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Mathieu Salzmann, Alexandre Massoud Alahi, Megh Hiren Shukla

Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

2024

Machine Learning Security in Industry: A Quantitative Survey

Kathrin Grosse

Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze at ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Causal inference with recurrent and competing events

Mats Julius Stensrud, Pal Christie Ryalen, Matias Janvin

Many research questions concern treatment effects on outcomes that can recur several times in the same individual. For example, medical researchers are interested in treatment effects on hospitalizations in heart failure patients and sports injuries in ath ...

SPRINGER2023

Visual Focus of Attention Estimation in 3D Scene with an Arbitrary Number of Targets

Jean-Marc Odobez, Rémy Alain Siegfried

Visual Focus of Attention (VFOA) estimation in conversation is challenging as it relies on difficult to estimate information (gaze) combined with scene features like target positions and other contextual information (speaking status) allowing to disambigua ...

IEEE COMPUTER SOC2021

Data-Aware Privacy-Preserving Machine Learning

Aleksei Triastcyn

In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...

EPFL2020

Optimal Stochastic Sensor Error Modeling based on Actual Impact on Quality of GNSS-INS Integrated Navigation

Jan Skaloud, Stéphane Guerrier, Mehran Khaghani

Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...

2019

A power-balance model of the density limit in fusion plasmas: application to the L-mode tokamak

Olivier Sauter, Ambrogio Fasoli, Basil Duval, Martinus Adela Maria Gijs, Richard Pitts, Stefano Coda, Henri Weisen, Yves Martin, Yann Camenen, Jan Horacek, Patrick Blanchard, Javier García Hernández, Duccio Testa, Marco Wischmeier, Nicola Vianello, Mikhail Maslov, Alessandro Pau, Davide Galassi, Antonio José Pereira de Figueiredo, Liang Yao, Dalziel Joseph Wilson, Cristian Sommariva, Jonathan Graves, Federico Nespoli, Hamish William Patten, Samuel Lanthaler, David Pfefferlé, Jonathan Marc Philippe Faustin

A power-balance model, with radiation losses from impurities and neutrals, gives a unified description of the density limit (DL) of the stellarator, the L-mode tokamak, and the reversed field pinch (RFP). The model predicts a Sudo-like scaling for the stel ...

IOP Publishing Ltd2019

Dealing with Correlations in Discrete Choice Models

Anna Fernández Antolín

The focus of this thesis is to develop methods to address research challenges related to correlation patterns in discrete choice models. In the context of correlations within alternatives, we extend the novel methodology of the multiple indicator solution ...

EPFL2018

Parameter Estimation with GNSS-Reflectometry and GNSS Synthetic Aperture Techniques

Miguel Angel Ribot Sanfelix

Aside from intentional interference, multipath is the most significant error source for Global Navigation Satellite Systems (GNSS) receivers in many operational scenarios. In this thesis, we study the multipath estimation from two different perspectives: t ...

EPFL2018

Joint Estimation Of The Room Geometry And Modes With Compressed Sensing

Pierre Vandergheynst, Hervé Lissek, Helena Peic Tukuljac, Vu Thach Pham

Acoustical behavior of a room for a given position of microphone and sound source is usually described using the room impulse response. If we rely on the standard uniform sampling, the estimation of room impulse response for arbitrary positions in the room ...

IEEE2018

Efficient Analysis of Confined Guided Modes in Phoxonic Crystal Slabs

Today's standard fabrication processes are just capable of manufacturing slab of photonic and phononic crystals, so an efficient method for analysis of these crystals is indispensable. Plane wave expansion (PWE) as a widely used method in studying photonic ...

IEEE Institute of Electrical and Electronics Engineers2017

Estimation of the Armature Leakage Reactance using the Constant Excitation Test

Basile Kawkabani

The adoption of the best available estimate for the stator Leakage reactance is the first step in several equivalent circuit of synchronous machine parameter estimation. However, there is no specific test for its direct measurement. This paper presents a s ...

IEEE2016

Bed load fluctuations in a steep channel

Anton Schleiss, Mário Jorge Rodrigues Pereira Da Franca, Tamara Ghilardi

Bedload transport rate fluctuations have been observed over time in steep rivers and flumes with wide grain size distributions even under constant sediment feeding and water discharge. The observed bedload transport rate pulses are periodic and a consequen ...

American Geophysical Union2014

Statistical Inference for Partially Observed Stochastic Epidemics

Andrea Kraus

This work is concerned with the estimation of the spreading potential of the disease in the initial stages of an epidemic. A speedy and accurate estimation is important for determining whether or not interventions are necessary to prevent a major outbreak. ...

EPFL2013

Robust Parameter Estimation for the Ornstein-Uhlenbeck Process

Sonja Rieder

In this thesis, we treat robust estimation for the parameters of the Ornstein–Uhlenbeck process, which are the mean, the variance, and the friction. We start by considering classical maximum likelihood estimation. For the simulation study, where we also in ...

EPFL2012

Approaches on the Thermal Management and Parameter Estimation of Solid Oxide Fuel Cells and their Systems

Leonidas Tsikonis

Solid Oxide Fuel Cells (SOFCs) are electrochemical devices that convert chemical energy from fuel directly into electrical and thermal energy. They present high electrical efficiency and because of this feature they are considered to be an important power ...

EPFL2011

Exponential Natural Evolution Strategies

Daniël Pieter Wierstra

The family of natural evolution strategies (NES) offers a principled approach to real-valued evolutionary optimization by following the natural gradient of the expected fitness. Like the well-known CMA-ES, the most competitive algorithm in the field, NES c ...

2010

Statistical analysis of clusters of extreme events

Mária Süveges

The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...

EPFL2009

Les mathématiques financières robustes, le maritime et les FFA

Powerful mathematical tools have been developed for trading in stocks and bonds, but other markets that are equally important for the globalized world have to some extent been neglected. We decided to study the shipping market as an new area of development ...

EPFL2008