Léonard Boussioux

According to our database, Léonard Boussioux authored at least 24 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression.

Léonard Boussioux, Alexandre Jacquillat, Ryne Reger, Jacob Wachspress

CoRR, May, 2026

Probing Neural TSP Representations for Prescriptive Decision Support.

Reuben Narad, Léonard Boussioux, Michael Wagner

CoRR, February, 2026

2025

SOLID: a Framework of Synergizing Optimization and LLMs for Intelligent Decision-Making.

Yinsheng Wang, Tario G. You, Léonard Boussioux, Shan Liu

CoRR, November, 2025

Mechanistic Interpretability for Neural TSP Solvers.

Reuben Narad, Léonard Boussioux, Michael Wagner

CoRR, October, 2025

Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations.

Jacquelin Lane, Léonard Boussioux, Charles Ayoubi, Yinghao Chen, Pei-Hsin Wang, Camila Lin, Rebecca Spens, Pooja Wagh

Proceedings of the 46th International Conference on Information Systems, 2025

Socratic Iterative Reasoning: Enhancing LLM Decision-Making in the Beer Game Supply Chain.

Léonard Boussioux, Andrew Chen, Ming Fan, Apurva Jain

Proceedings of the 46th International Conference on Information Systems, 2025

Enhancing Decision Making Through the Integration of Large Language Models and Operations Research Optimization.

Segev Wasserkrug, Léonard Boussioux, Dick den Hertog, Farzaneh Mirzazadeh, S. Ilker Birbil, Jannis Kurtz, Donato Maragno

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Holistic deep learning.

Dimitris Bertsimas, Kimberly Villalobos Carballo, Léonard Boussioux, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov

Mach. Learn., January, 2024

From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifesto.

Segev Wasserkrug, Léonard Boussioux, Dick den Hertog, Farzaneh Mirzazadeh, S. Ilker Birbil, Jannis Kurtz, Donato Maragno

CoRR, 2024

The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations.

Charles Ayoubi, Léonard Boussioux, Yinghao Chen, Justin Ho, Katherine Jackson, Jacquelin Lane, Camila Lin, Rebecca Spens

Proceedings of the 45th International Conference on Information Systems, 2024

2023

Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach.

Dimitris Bertsimas, Léonard Boussioux

CoRR, 2023

Reducing Air Pollution through Machine Learning.

Dimitris Bertsimas, Léonard Boussioux, Cynthia Zeng

CoRR, 2023

2022

Integrated multimodal artificial intelligence framework for healthcare applications.

Luis R. Soenksen, Yu Ma, Cynthia Zeng, Léonard Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael Lingzhi Li, Ignacio Fuentes, Dimitris Bertsimas

npj Digit. Medicine, 2022

TabText: a Systematic Approach to Aggregate Knowledge Across Tabular Data Structures.

Dimitris Bertsimas, Kimberly Villalobos Carballo, Yu Ma, Liangyuan Na, Léonard Boussioux, Cynthia Zeng, Luis R. Soenksen, Ignacio Fuentes

CoRR, 2022

2021

Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification.

Charles A. Kantor, Marta Skreta, Brice Rauby, Léonard Boussioux, Emmanuel Jehanno, Alexandra Luccioni, David Rolnick, Hugues Talbot

CoRR, 2021

Combating False Negatives in Adversarial Imitation Learning.

Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio

Proceedings of the International Joint Conference on Neural Networks, 2021

Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks.

Charles A. Kantor, Léonard Boussioux, Brice Rauby, Hugues Talbot

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction.

Charles A. Kantor, Léonard Boussioux, Brice Rauby, Hugues Talbot

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Hurricane Forecasting: A Novel Multimodal Machine Learning Framework.

Léonard Boussioux, Cynthia Zeng, Théo Guénais, Dimitris Bertsimas

CoRR, 2020

oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions.

David Venuto, Jhelum Chakravorty, Léonard Boussioux, Junhao Wang, Gavin McCracken, Doina Precup

CoRR, 2020

Asymptotic Cross-Entropy Weighting and Guided-Loss in Supervised Hierarchical Setting using Deep Attention Network.

Charles A. Kantor, Brice Rauby, Léonard Boussioux, Emmanuel Jehanno, André-Philippe Drapeau Picard, Maxim Larrivée, Hugues Talbot

Proceedings of the AAAI Fall Symposium on AI for Social Good, 2020

Combating False Negatives in Adversarial Imitation Learning (Student Abstract).

Konrad Zolna, Chitwan Saharia, Léonard Boussioux, David Yu-Tung Hui, Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Yoshua Bengio

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Avoidance Learning Using Observational Reinforcement Learning.

David Venuto, Léonard Boussioux, Junhao Wang, Rola Dali, Jhelum Chakravorty, Yoshua Bengio, Doina Precup

CoRR, 2019

InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification.

Léonard Boussioux, Tomás Giro-Larraz, Charles Guille-Escuret, Mehdi Cherti, Balázs Kégl

CoRR, 2019