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Thibaut Vidal

@vidalthi.bsky.social
168 followers 63 following 16 posts

Professor & SCALE-AI Chair at MAGI Polytechnique Montréal IVADO Labs Scientific Advisor Sharing content about #ORMS & #Trustworthy #MachineLearning Open-source codes: github.com/vidalt

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Thibaut Vidal @vidalthi.bsky.social · 22/10/2025
Propulsing vehicle routing into space... At IVADO's Digital Futures Event, my brilliant postdoc and collaborator Théo Guyard will show how #Optimization & #MachineLearning meet orbital dynamics to clean up space debris, in collaboration with NASA Ames Research Center.🚀 ivado.ca/en/events/iv...
ivado.ca
IVADO Digital Futures 2025 | IVADO
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Thibaut Vidal @vidalthi.bsky.social · 16/01/2025
Work done at the SCALE-AI Chair at @polymtl.bsky.social with my fabulous co-authors Arthur Ferraz, Quentin Cappart, Axel Parmentier, Alexandre Forel, and Cheikh Ahmed... Happy #ORMS, #StrategicOptimization, and #MachineLearning, everyone!
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Thibaut Vidal @vidalthi.bsky.social · 16/01/2025
Related links: 🔗Paper 1: arxiv.org/pdf/2402.06040 🔗Paper 2 (NeurIPS 2024): arxiv.org/pdf/2412.08287 🔗Source code: github.com/vidalt/Distr...
github.com
GitHub - vidalt/Districting-Routing: Source code associated with the paper "Deep Learning for Data-Driven Districting-and-Routing", authored by A. Ferraz, Q. Cappart, and T. Vidal
Source code associated with the paper "Deep Learning for Data-Driven Districting-and-Routing", authored by A. Ferraz, Q. Cappart, and T. Vidal - vidalt/Districting-Routing
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Thibaut Vidal @vidalthi.bsky.social · 16/01/2025
How can GNNs be harnessed for an efficient strategic optimization of delivery districts using ML+OR pipelines and end-to-end learning? Check Data Skeptic's latest podcast discussing two of our recent works on this topic (my intervention starts around 5:00): open.spotify.com/episode/3GAP...
open.spotify.com
Optimizing Supply Chains with GNN
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Thibaut Vidal @vidalthi.bsky.social · 10/01/2025
Stay tuned as we regularly share new discoveries on trustworthy #MachineLearning in connection with #GraphTheory, #ORMS, and Combinatorial Optimization. All the related papers are openly accessible, as well as the source codes: github.com/vidalt Thanks for following us! 🙌
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Thibaut Vidal @vidalthi.bsky.social · 10/01/2025
This study was funded by SCALE-AI Canada through its "Research Chairs" program and Polytechnique Montréal (@polymtl.bsky.social). It has been a privilege to collaborate with the brilliant Julien Ferry, Ricardo Fukasawa, and Timothée Pascal on this!
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Thibaut Vidal @vidalthi.bsky.social · 10/01/2025
Until February 14, 2025, you can vote for your favorite discovery on the list! If you would like to support our project, "L’intelligence artificielle : toujours confidentielle?", cast your vote here: www.quebecscience.qc.ca/decouverte20...
quebecscience.qc.ca
Votez pour votre découverte préférée!
Notre jury a sélectionné les 10 découvertes québécoises les plus impressionnantes de la dernière année. À votre tour de choisir la découverte qui vous surprend ou vous inspire le plus.
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Thibaut Vidal @vidalthi.bsky.social · 10/01/2025
Our work stood out for its critical focus on AI safety, with the jury emphasizing: "The rapid development of AI sometimes comes at the expense of public safety. Highlighting the risks of data non-confidentiality is a crucial step in establishing ethical guidelines."
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Thibaut Vidal @vidalthi.bsky.social · 10/01/2025
Hot off the press! Our research on the risks of training-data reconstruction from random forest models* has just been nominated on Quebec Science's (@quebecscience.bsky.social) Top 10 Scientific Discoveries of 2024! 🌟 🚀 www.quebecscience.qc.ca/sciences/les...
quebecscience.qc.ca
L’intelligence artificielle : toujours confidentielle ? - Québec Science
Les modèles d’intelligence artificielle peuvent à l’occasion se montrer trop bavards ! En les étudiant, on peut parfois reconstituer des données confidentielles qui ont servi à leur entraînement.
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Thibaut Vidal @vidalthi.bsky.social · 02/12/2024
Alice Gorgé just completed her research internship at the SCALE AI Chair at Polytechnique Montréal on the privacy risks of ML models. She has just received the prestigious Louis-Edouard Rivot medal, an honor given annually to Polytechnique Paris (X) students who excel in their research work! 😎
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Thibaut Vidal @vidalthi.bsky.social · 28/11/2024
All the source code and material to reproduce the experiments is available under an MIT license at github.com/alexforel/Ad.... Many thanks to my fabulous coauthors as well as SCALE-AI and @polymtl.bsky.social for the research support. Happy optimization, everyone... 😎
github.com
GitHub - alexforel/AdaptiveCC: Code for paper on "Adaptive Partitioning for Chance-Constrained Problems"
Code for paper on "Adaptive Partitioning for Chance-Constrained Problems" - alexforel/AdaptiveCC
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Thibaut Vidal @vidalthi.bsky.social · 28/11/2024
In a nutshell, the method works by iteratively refining and merging scenario sets to obtain tightened bounds. Convergence is guaranteed over a finite number of iterations, and we experimentally measure very significant speed-ups over direct solution approaches.
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Thibaut Vidal @vidalthi.bsky.social · 28/11/2024
Interested in solving chance-constrained optimization problems at scale? Buckle-up, the most recent work of Marius Roland and Alexandre Forel (optimization-online.org?p=25061) is now in the press at SIAM JOpt... Congratulations on this excellent work! 🚀 #ORMS #Stochastic #Optimization
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Thibaut Vidal @vidalthi.bsky.social · 27/11/2024
Last week was my first time in a radio studio, joining @matthieudugal.bsky.social & Moteur de Recherche on Radio Canada. What an experience! The vibe was fantastic & there's something so exciting about chatting with the columnists and sharing cool science facts🎙️🤩 ici.radio-canada.ca/ohdio/premie...
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Thibaut Vidal @vidalthi.bsky.social · 23/11/2024
Hello, world! Hummm... hello, blue sky? 😏
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Thibaut Vidal @vidalthi.bsky.social · 22/11/2024
A bit late to this party... but can you add me? ;)
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