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Items where Author is "Gasse, Maxime"

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Number of items: 13.

G

Gasse, M., & Lodi, A. (2022). Machine Learning for Combinatorial Optimization. In Pardalos, P. M., & Prokopyev, O. A. (eds.), Encyclopedia of Optimization (pp. 1-13). External link

Gupta, P., Gasse, M., Khalil, E. B., Kumar, M. P., Lodi, A., & Bengio, Y. (2020, December). Hybrid models for learning to branch [Paper]. 34th Conference on neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada (11 pages). External link

Gupta, P., Gasse, M., Khalil, E. B., Kumar, M. P., Lodi, A., & Bengio, Y. (2020, December). Supplement: Hybrid models for learning to branch [Paper]. 34th Conference on neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada (8 pages). External link

Gasse, M., Chetelat, D., Ferroni, N., Charlin, L., & Lodi, A. (2019, December). Exact Combinatorial Optimization with Graph Convolutional Neural Networks [Paper]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, B.-C. (13 pages). External link

M

Müller, B., Muñoz, G., Gasse, M., Gleixner, A., Lodi, A., & Serrano, F. (2022). On generalized surrogate duality in mixed-integer nonlinear programming. Mathematical Programming, 2021(1-2), 1-30. Available

Milecki, L., Porée, J., Belgharbi, H., Bourquin, C., Damseh, R., Delafontaine-Martel, P., Lesage, F., Gasse, M., & Provost, J. (2021). A deep learning framework for spatiotemporal ultrasound localization microscopy. IEEE Transactions on Medical Imaging, 40(5), 1428-1437. External link

Müller, B., Muñoz, G., Gasse, M., Gleixner, A., Lodi, A., & Serrano, F. (2020, June). On Generalized Surrogate Duality in Mixed-Integer Nonlinear Programming [Paper]. 21st International Conference on Integer Programming and Combinatorial Optimization (IPCO 2020), London, United Kingdom. External link

R

Rastgar Amini, F., Contardo, C., Desaulniers, G., & Gasse, M. (2025). Learning to enumerate shifts for large-scale flexible personnel scheduling problems. Journal of Scheduling, 19 pages. External link

Rauby, B., Xing, P., Porée, J., Gasse, M., & Provost, J. (2025). Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy. IEEE Transactions on Image Processing, 34, 2367-2378. External link

Rauby, B., Xing, P., Gasse, M., & Provost, J. (2024). Deep learning in ultrasound localization microscopy : applications and perspectives. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 3462299 (23 pages). Available

Rastgar Amini, F., Contardo, C., Desaulniers, G., & Gasse, M. (2022). Learning to enumerate shifts for large-scale flexible personnel scheduling problems. (Technical Report n° G-2022-29). External link

S

Scavuzzo, L., Chetelat, D., Lodi, A., Chen, F. Y., Gasse, M., Yorke-Smith, N., & Aardal, K. (2022, November). Learning to Branch with Tree MDPs [Poster]. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. External link

Scavuzzo, L., Chetelat, D., Lodi, A., Chen, F. Y., Gasse, M., Yorke-Smith, N., & Aardal, K. (2022, November). Learning to Branch with Tree MDPs [Presentation]. In 36th Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA. External link

List generated on: Thu Jun 19 06:22:27 2025 EDT