Publications

089 Levers and limitations of artificial intelligence (AI) to support the assessment and implementation of shared decision making (SDM): perspectives of key stakeholders

Anik Giguère

Adrian Edwards

Denitza Williams

France Légaré

Natalie Joseph-Williams

Samira Abbasgholizadeh-Rahimi

Karina Prévost

Marie-Clare Hunter

Anna Torrens-Burton

Justine Laloux

2024-06-30

International Symposium on Data Mining (publié)

doi.org

169Yb-based high dose rate intensity modulated brachytherapy for focal treatment of prostate cancer

Maude Robitaille

Cynthia Ménard

Gabriel Famulari

Dominic Béliveau-Nadeau

S. Enger

2024-06-30

Brachytherapy (publié)

doi.org

Accelerated Benders Decomposition and Local Branching for Dynamic Maximum Covering Location Problems

Steven Lamontagne

Margarida Carvalho

Ribal Atallah

The maximum covering location problem (MCLP) is a key problem in facility location, with many applications and variants. One such variant is… (voir plus) the dynamic (or multi-period) MCLP, which considers the installation of facilities across multiple time periods. To the best of our knowledge, no exact solution method has been proposed to tackle large-scale instances of this problem. To that end, in this work, we expand upon the current state-of-the-art branch-and-Benders-cut solution method in the static case, by exploring several acceleration techniques. Additionally, we propose a specialised local branching scheme, that uses a novel distance metric in its definition of subproblems and features a new method for efficient and exact solving of the subproblems. These methods are then compared through extensive computational experiments, highlighting the strengths of the proposed methodologies.

2024-06-30

Computers & Operations Research (publié)

doi.org

arxiv.org

Deep learning based vessel arrivals monitoring via autoregressive statistical control charts

Sara El Mekkaoui

Ghait Boukachab

Loubna Benabbou

Abdelaziz Berrado

2024-06-30

WMU Journal of Maritime Affairs (JoMA) (publié)

doi.org

Imagining a Future of Designing with AI: Dynamic Grounding, Constructive Negotiation, and Sustainable Motivation

Priyan Vaithilingam

Ian Arawjo

Elena L. Glassman

2024-06-30

Designing Interactive Systems Conference (publié)

doi.org

arxiv.org

Do LLMs Meet the Needs of Software Tutorial Writers? Opportunities and Design Implications

Avinash Bhat

Disha Shrivastava

Jin L.C. Guo

Creating software tutorials involves developing accurate code examples and explanatory text that engages and informs the reader. Large Langu… (voir plus)age Models (LLMs) demonstrate a strong capacity to generate both text and code, but their potential to assist tutorial writing is unknown. By interviewing and observing seven experienced writers using OpenAI playground as an exploration environment, we uncover design opportunities for leveraging LLMs in software tutorial writing. Our findings reveal background research, resource creation, and maintaining quality standards as critical areas where LLMs could significantly assist writers. We observe how tutorial writers generated tutorial content while exploring LLMs’ capabilities, formulating prompts, verifying LLM outputs, and reflecting on interaction goals and strategies. Our observation highlights that the unpredictability of LLM outputs and unintuitive interface design contributed to skepticism about LLM’s utility. Informed by these results, we contribute recommendations for designing LLM-based tutorial writing tools to mitigate usability challenges and harness LLMs’ full potential.

2024-06-30

Conference on Designing Interactive Systems (publié)

doi.org

A logistics provider’s profit maximization facility location problem with random utility maximizing followers

David Pinzon Ulloa

Emma Frejinger

Bernard Gendron

2024-06-30

Computers & Operations Research (publié)

doi.org

arxiv.org

One-shot Learning for MIPs with SOS1 Constraints

Charly Robinson La Rocca

Jean-François Cordeau

Emma Frejinger

2024-06-30

Operations Research Forum (publié)

doi.org

arxiv.org

Overcoming Boundaries: Interdisciplinary Challenges and Opportunities in Cognitive Neuroscience

Arnaud Brignol

Anita Paas

Luis Sotelo-Castro

David St-Onge

Giovanni Beltrame

Emily B.J. Coffey

2024-06-30

Neuropsychologia (publié)

doi.org

Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning

Georg Pichler

Marco Romanelli

Leonardo Rey Vega

Pablo Piantanida

Federated Learning is expected to provide strong privacy guarantees, as only gradients or model parameters but no plain text training data i… (voir plus)s ever exchanged either between the clients or between the clients and the central server. In this paper, we challenge this claim by introducing a simple but still very effective membership inference attack algorithm, which relies only on a single training step. In contrast to the popular honest-but-curious model, we investigate a framework with a dishonest central server. Our strategy is applicable to models with ReLU activations and uses the properties of this activation function to achieve perfect accuracy. Empirical evaluation on visual classification tasks with MNIST, CIFAR10, CIFAR100 and CelebA datasets show that our method provides perfect accuracy in identifying one sample in a training set with thousands of samples. Occasional failures of our method lead us to discover duplicate images in the CIFAR100 and CelebA datasets.

2024-06-30

IEEE Transactions on Dependable and Secure Computing (publié)

doi.org

arxiv.org

Surface water temperature observations and ice phenology estimations for 1.4 million lakes globally

Maartje C. Korver

Bernhard Lehner

Jeffrey A. Cardille

Laura Carrea

2024-06-30

Remote Sensing of Environment (publié)

doi.org