Publications associées à Lancet: A self-correcting Latency Measuring Tool

Publications associées (39)

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

Igor Rodionov, Anthony Christopher Davison

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

Oxford Univ Press2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Search for the lepton flavour violating decays B0→e±μ∓ and B0s→e±μ∓ with LHCb Run 2 data

Sebastian Schulte

A large variety of new physics models suggest that the rates for lepton flavour violating

b

-hadron decays may be much higher than predicted in the Standard Model, which leads to a high interest in the search for such decays. This thesis presents the se ...

EPFL2024

Using Gaming Footage as a Source of Internet Latency Information

Aikaterini Argyraki, Catalina Paz Alvarez Inostroza

Keeping track of Internet latency is a classic measurement problem. Open measurement platforms like RIPE Atlas are a great solution, but they also face challenges: preventing network overload that may result from uncontrolled active measurements, and maint ...

2023

Maximum likelihood bolometry for ASDEX upgrade experiments

Olivier Claude Martin Février, Riccardo Rossi

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, h ...

Iop Publishing Ltd2023

Bias free multiobjective active learning for materials design and discovery

Berend Smit, Kevin Maik Jablonka, Shi-Lin Wang

The design rules for materials are clear for applications with a single objective. For most applications, however, there are often multiple, sometimes competing objectives where there is no single best material and the design rules change to finding the se ...

Nature Research2021

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

Jérôme Chenal, Vitor Pessoa Colombo, Jürg Utzinger

Background Universal access to basic sanitation remains a global challenge, particularly in low- and middle-income countries. Efforts are underway to improve access to sanitation in informal settlements, often through shared facilities. However, access to ...

2023

Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Joseph Chadi Benoit Lemaitre

Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R-eff) using a mechanistic metapopulation model and associ ...

Nature Research2021

Leukocyte Count and Coronary Artery Disease Events in People With Human Immunodeficiency Virus: A Longitudinal Study

Jacques Fellay, Christian Axel Wandall Thorball

Leukocyte count is associated with coronary artery disease (CAD) events in the general population. Here we show that leukocytes are independently associated with CAD events in people with HIV in Switzerland, after adjusting for traditional and HIVrelated r ...

OXFORD UNIV PRESS INC2023

Practical issues with modeling extreme Brazilian rainfall

Anthony Christopher Davison

Accurately quantifying extreme rainfall is important for the design of hydraulic structures, for flood mapping and zoning and for disaster management. In order to produce maps of estimates of 25-year rainfall return levels in Brazil, we selected 893 shorte ...

BRAZILIAN STATISTICAL ASSOCIATION2021

Collaborative Sampling in Generative Adversarial Networks

Alexandre Massoud Alahi, Yuejiang Liu, Parth Ashit Kothari

The standard practice in Generative Adversarial Networks (GANs) discards the discriminator during sampling. However, this sampling method loses valuable information learned by the discriminator regarding the data distribution. In this work, we propose a co ...

2020

A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles

Rico Krüger

This paper i) compares parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian logit models and ii) applies these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV ...

2020

Flow Time Scheduling and Prefix Beck-Fiala

Ola Nils Anders Svensson, Lars Rohwedder

We relate discrepancy theory with the classic scheduling problems of minimizing max flow time and total flow time on unrelated machines. Specifically, we give a general reduction that allows us to transfer discrepancy bounds in the prefix Beck-Fiala (bound ...

ASSOC COMPUTING MACHINERY2022

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

Beating the I/O Bottleneck: A Case for Log-Structured Virtual Disks

Vojtech Aschenbrenner

With the increasing dominance of SSDs for local storage, today's network mounted virtual disks can no longer offer competitive performance. We propose a Log-Structured Virtual Disk (LSVD) that couples log-structured approaches at both the cache and storage ...

ASSOC COMPUTING MACHINERY2022

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Kerstin Preuschoff, Leyla Loued-Khenissi

Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivat ...

2020

Semi-supervised Active Salient Object Detection

Gonzalo Orejas Guinea, Tong Zhang

In this paper, we propose a novel semi-supervised active salient object detection (SOD) method that actively acquires a small subset of the most discriminative and representative samples for labeling. Two main contributions have been made to prevent the me ...

ELSEVIER SCI LTD2022

Is There a Cap on Longevity? A Statistical Review

Anthony Christopher Davison, Léo Raymond-Belzile

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

ANNUAL REVIEWS2022

From Data to Decisions: Distributionally Robust Optimization is Optimal

Daniel Kuhn, Peyman Mohajerin Esfahani

We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...

2021

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022