Publications

Enjeux éthiques de l’IA en santé - Fiche 4
Joé T. Martineau
Frédérique Romy Godin
Janine Badr
Alexandre Castonguay
Martin Cousineau
Philippe Després
Aude Motulsky
Jean Noel Nikiema
Cécile Petitgand
Catherine Régis
La présente fiche propose une revue des différents enjeux éthiques liés au développement et à l’utilisation des technologies d’int… (see more)elligence artificielle dans le milieu de la santé, en trois parties. D’abord, nous aborderons les enjeux éthiques liés à l’exploitation de données massives nécessaires à l’entrainement des algorithmes de l’IA. Ensuite, nous présenterons les principaux enjeux éthiques liés au développement et à l’utilisation des SIA en santé, en abordant la façon dont ces systèmes impactent nos vies ainsi que l’environnement physique et social dans lequel nous vivons. Nous présenterons finalement les principales initiatives nationales et internationales en matière d’éthique de l’IA et de la gestion des données, fruits et reflets d’une réflexion globale sur ces sujets. Ces initiatives ont notamment proposé des lignes directrices et principes normatifs servant de guides pour le développement de technologies de l’IA éthiques et responsables Il s'agit de la quatrième fiche d'une série de 4 développée dans le cadre d'un mandat réalisé pour le Ministère de la Santé et des Services sociaux du Québec (MSSS).
2022-03-01
(published)
doi.org
Guidelines for the Computational Testing of Machine Learning approaches to Vehicle Routing Problems
Luca Accorsi
Andrea Lodi
Daniele Vigo
2022-03-01
Operations Research Letters (published)
doi.org
arxiv.org
Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder.
Christine Ecker
Charlotte M. Pretzsch
Anke Bletsch
Caroline Mann
Tim Schaefer
Sara Ambrosino
Julian Tillmann
Afsheen Yousaf
Andreas Chiocchetti
Michael V. Lombardo
Varun Warrier
Nico Bast
Carolin Moessnang
Sarah Baumeister
Flavio Dell’Acqua
Dorothea L. Floris
Mariam Zabihi
Andre Marquand
Freddy Cliquet
Claire Leblond … (see 19 more)
Clara A. Moreau
Nick Puts
Tobias Banaschewski
Emily J. H. Jones
Luke Mason
Sven Bölte
Andreas Meyer-Lindenberg
Antonio Persico
Sarah Durston
Simon Baron-Cohen
Will Spooren
Eva Loth
Christine M. Freitag
Tony Charman
Guillaume Dumas
Thomas Bourgeron
Christian Beckmann
Jan K. Buitelaar
Declan Murphy
2022-03-01
American Journal of Psychiatry (published)
doi.org
JANOS: An Integrated Predictive and Prescriptive Modeling Framework
David Bergman
Teng Huang
Philip Brooks
Andrea Lodi
Arvind U. Raghunathan
Business research practice is witnessing a surge in the integration of predictive modeling and prescriptive analysis. We describe a modeling… (see more) framework JANOS that seamlessly integrates the two streams of analytics, allowing researchers and practitioners to embed machine learning models in an end-to-end optimization framework. JANOS allows for specifying a prescriptive model using standard optimization modeling elements such as constraints and variables. The key novelty lies in providing modeling constructs that enable the specification of commonly used predictive models within an optimization model, have the features of the predictive model as variables in the optimization model, and incorporate the output of the predictive models as part of the objective. The framework considers two sets of decision variables: regular and predicted. The relationship between the regular and the predicted variables is specified by the user as pretrained predictive models. JANOS currently supports linear regression, logistic regression, and neural network with rectified linear activation functions. In this paper, we demonstrate the flexibility of the framework through an example on scholarship allocation in a student enrollment problem and provide a numeric performance evaluation. Summary of Contribution. This paper describes a new software tool, JANOS, that integrates predictive modeling and discrete optimization to assist decision making. Specifically, the proposed solver takes as input user-specified pretrained predictive models and formulates optimization models directly over those predictive models by embedding them within an optimization model through linear transformations.
2022-03-01
INFORMS Journal on Computing (published)
doi.org
arxiv.org
Multistep networks for roll force prediction in hot strip rolling mill
Shuh-Rong Shen
Denzel Guye
Xiaopin Ma
Sheng‐Jie Yue
Narges Armanfard
2022-03-01
Machine Learning with Applications (published)
doi.org
Multistep networks for roll force prediction in hot strip rolling mill
Shuh-Rong Shen
Denzel Guye
Xiaoping Ma
S. Yue
Narges Armanfard
2022-03-01
Machine Learning with Applications (published)
doi.org
Single Allocation Hub Location with Heterogeneous Economies of Scale
Borzou Rostami
Masoud Chitsaz
Okan Arslan
Gilbert Laporte
Andrea Lodi
2022-03-01
Operations Research (published)
doi.org
Software-Engineering Design Patterns for Machine Learning Applications
Hironori Washizaki
Foutse Khomh
Yann‐Gaël Guéhéneuc
Hironori Takeuchi
Naotake Natori
Takuo Doi
Satoshi Okuda
In this study, a multivocal literature review identified 15 software-engineering design patterns for machine learning applications. Findings… (see more) suggest that there are opportunities to increase the patterns’ adoption in practice by raising awareness of such patterns within the community.
2022-03-01
Computer (published)
doi.org
Software-Engineering Design Patterns for Machine Learning Applications
Hironori Washizaki
Foutse Khomh
Yann‐Gaël Guéhéneuc
Hironori Takeuchi
Naotake Natori
Takuo Doi
Satoshi Okuda
In this study, a multivocal literature review identified 15 software-engineering design patterns for machine learning applications. Findings… (see more) suggest that there are opportunities to increase the patterns’ adoption in practice by raising awareness of such patterns within the community.
2022-03-01
Computer (published)
doi.org
The Role of Robotics in Achieving the United Nations Sustainable Development Goals - The Experts' Meeting at the 2021 IEEE/RSJ IROS Workshop [Industry Activities]
Vincent Mai
Bram Vanderborght
Tamás P. Haidegger
Alaa M. Khamis
Niraj Bhargava
Dominik B. O. Boesl
K. Gabriels
An Jacobs
AJung Moon
R. Murphy
Yasushi Nakauchi
Edson Prestes
Bhavani Rao R.
Ricardo Vinuesa
Carl-Maria Mörch
2022-03-01
IEEE Robotics Autom. Mag. (published)
doi.org
The Role of Robotics in Achieving the United Nations Sustainable Development Goals - The Experts' Meeting at the 2021 IEEE/RSJ IROS Workshop [Industry Activities]
Vincent Mai
Bram Vanderborght
Tamás Haidegger
Alaa Khamis
Niraj Bhargava
Dominik B.O. Boesl
Katleen Gabriels
An Jacobs
AJung Moon
Robin Murphy
Yasushi Nakauchi
Edson Prestes
Bhavani Rao R.
Ricardo Vinuesa
Carl-Maria Mörch
The development and deployment of robotic technologies can have an important role in efforts to achieve the United Nations’ (UN) Sustainab… (see more)le Development Goals (SDGs)—with both enabling and inhibiting impacts. During a workshop at the 2021 IEEE/Robotics Society of Japan International Conference on Intelligent Robots and Systems (IROS 2021), experts from various disciplines analyzed the role of robotics in achieving the SDGs. This article provides a summary of the most important outcomes of the workshop. During the workshop panels, the variety of roles that robots can play in enabling the SDGs was underlined. The panelists discussed the challenges to the adoption of robots and to their deployment at their full potential. The probable undesirable effects of robots were also considered, and the panelists suggested approaches to correctly design SDG-relevant robotic solutions. Governance frameworks were also discussed, with respect to their contents as well as the challenges to build them. The role of military funding was briefly analyzed. Finally, several proposals for actions and policies were made. The contents of the workshop, including contributing papers and videos from the panelists, as well as additional information about future initiatives regarding robotics and the SDGs, are available at www.sustainablerobotics.org.
2022-03-01
IEEE Robotics Autom. Mag. (published)
doi.org
Combining Modular Skills in Multitask Learning
Edoardo Ponti
Alessandro Sordoni
Siva Reddy
2022-02-28
ArXiv (preprint)
arxiv.org
arxiv.org