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Tackling Peer-to-Peer Discrimination in the Sharing Economy

Publications associées (31)

A Phylogeny-aware GWAS Framework to Correct for Heritable Pathogen Effects on Infectious Disease Traits

Jacques Fellay, Christian Axel Wandall Thorball

Infectious diseases are particularly challenging for genome-wide association studies (GWAS) because genetic effects from two organisms (pathogen and host) can influence a trait. Traditional GWAS assume individual samples are independent observations. Howev ...

OXFORD UNIV PRESS2022

How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19

Mats Julius Stensrud

In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that h ...

2021

Advances in Bias-aware Recommendation on the Web

Mirko Marras

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

ASSOC COMPUTING MACHINERY2021

Countering Bias in Personalized Rankings From Data Engineering to Algorithm Development

Mirko Marras

This tutorial presents recent advances on the assessment and mitigation of data and algorithmic bias in personalized rankings. We first introduce fundamental concepts and definitions associated with bias issues, covering the state of the art and describing ...

IEEE COMPUTER SOC2021

Global Free-Energy Landscapes as a Smoothly Joined Collection of Local Maps

Michele Ceriotti, Gareth Aneurin Tribello, Federico Giberti

Enhanced sampling techniques have become an essential tool in computational chemistry and physics, where they are applied to sample activated processes that occur on a time scale that is inaccessible to conventional simulations. Despite their popularity, i ...

2021

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Scott William Pesme, Nicolas Henri Bernard Flammarion, Loucas Pillaud-Vivien

Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the dynamics of stochastic gradient descent over diagonal linear networks through i ...

2021

Controlling the rotation of drift tearing modes by biased electrode in ADITYA-U tokamak

Sameer Kumar, Abhijit Sen, Harshita Raj, Ankit Kumar, Rohit Kumar

The influence of background plasma poloidal rotation on the rotation frequency of the m/n = 2/1 drift tearing mode (DTM) has been studied in ADITYA-U tokamak. The poloidal rotation velocity of the background plasma in the ion diamagnetic direction is incre ...

2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

Forough Arabshahi, Antoine Bosselut

One of the challenges faced by conversational agents is their inability to identify unstated presumptions of their users' commands, a task trivial for humans due to their common sense. In this paper, we propose a zeroshot commonsense reasoning system for c ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

A systematic review of machine learning classification methodologies for modelling passenger mode choice

Michel Bierlaire, Ying Jin, Timothy Michael Hillel

Machine Learning (ML) approaches are increasingly being investigated as an alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These approaches have the potential to provide valuable insights into choice modelling research ques ...

ELSEVIER SCI LTD2021

High-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint model

Athanasios Nenes, Jennifer Kaiser

Ammonia (NH3) emissions have large impacts on air quality and nitrogen deposition, influencing human health and the well-being of sensitive ecosystems. Large uncertainties exist in the "bottom-up" NH3 emission inventories due to limited source information ...

Copernicus GmbH2021

Practical issues with modeling extreme Brazilian rainfall

Anthony Christopher Davison, Isolde Santos Previdelli, Paulo Vitor Da Costa Pereira

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