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Antoine Lesage-LandryDépartement de génie électrique
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Bélanger, O., Ben Yahia, O., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (mars 2024). Quality of Service-Constrained Online Routing in High Throughput Satellites [Communication écrite]. 2024 IEEE Aerospace Conference, Big Sky, MT, USA (9 pages). Lien externe
Daoust, O., Nayir, H., Azam, I., Lesage-Landry, A., & Karabulut Kurt, G. (juin 2024). Tensor-Based Space Debris Detection for Satellite Mega-constellations [Communication écrite]. 2024 IEEE International Conference on Communications Workshops (ICC Workshops 2024), Denver, CO, USA. Lien externe
Henriquez, R., Lesage-Landry, A., Taylor, J. A., Olivares, D., & Negrete-Pincetic, M. (novembre 2017). Managing load contract restrictions with online learning [Communication écrite]. IEEE Global Conference on Signal and Information Processing (GlobalSIP 2017), Montréal, Qc, Canada. Lien externe
Lupien, J.-L., & Lesage-Landry, A. (2025). Ex post conditions for the exactness of optimal power flow conic relaxations. Electric Power Systems Research, 238, 111130 (4 pages). Lien externe
Li, F., Kocar, I., & Lesage-Landry, A. (juillet 2024). A Rapid Method for Impact Analysis of Grid-edge Technologies on Power Distribution Networks [Communication écrite]. IEEE Power & Energy Society General Meeting (PESGM), Seattle, WA, USA. Lien externe
Li, F., Kocar, I., & Lesage-Landry, A. (2024). A Rapid Method for Impact Analysis of Grid-Edge Technologies on Power Distribution Networks. IEEE Transactions on Power Systems, 39(1), 1530-1542. Lien externe
Li, F., Campeau, É., Kocar, I., & Lesage-Landry, A. (2024). Inferring electric vehicle charging patterns from smart meter data for impact studies. (Rapport technique n° G-2024-02). Lien externe
Li, F., Campeau, É., Kocar, I., & Lesage-Landry, A. (2024). Inferring electric vehicle charging patterns from smart meter data for impact studies. Electric Power Systems Research, 235, 110789 (6 pages). Lien externe
Lesage-Landry, A., & Pallage, J. (2024). Online dynamic submodular optimization. Automatica, 167, 111758 (9 pages). Lien externe
Lesage-Landry, A., Pellerin, F., Callaway, D. S., & Taylor, J. A. (2023). Optimally scheduling public safety power shutoffs. Stochastic systems, 19 pages. Disponible
Lesage-Landry, A., & Callaway, D. S. (2023). Approximated multi-agent fitted Q iteration. Systems & Control Letters, 177, 105563 (10 pages). Lien externe
Li, F., Kocar, I., & Lesage-Landry, A. (juillet 2023). Mitigating Equipment Overloads due to Electric Vehicle Charging Using Customer Incentives [Communication écrite]. IEEE Power & Energy Society General Meeting (PESGM 2023), Orlando, FL, USA (5 pages). Lien externe
Lupien, J.-L., & Lesage-Landry, A. (2023). An Online Newton's Method for Time-Varying Linear Equality Constraints. IEEE Control Systems Letters, 7, 1423-1428. Lien externe
Li, F., Kocar, I., & Lesage-Landry, A. (2022). Rapid method for impact analysis of grid-edge technologies on power distribution networks. (Rapport technique n° 2022-45). Lien externe
Lesage-Landry, A., & Callaway, D. S. (2022). Batch reinforcement learning for network-safe demand response in unknown electric grids. Electric Power Systems Research, 212, 108375 (7 pages). Lien externe
Lesage-Landry, A., Taylor, J. A., & Callaway, D. S. (2021). Online convex optimization with binary constraints. IEEE Transactions on Automatic Control, 66(12), 6164-6170. Lien externe
Lesage-Landry, A., Taylor, J. A., & Shames, I. (2021). Second-order online nonconvex optimization. IEEE Transactions on Automatic Control, 66(10), 4866-4872. Lien externe
Lesage-Landry, A., & Callaway, D. S. (2020). Dynamic and distributed online convex optimization for demand response of commercial buildings. IEEE Control Systems Letters, 4(3), 632-637. Lien externe
Lesage-Landry, A., Chen, S., & Taylor, J. A. (2020). Estimating the frequency coupling matrix from network measurements. IEEE Transactions on Control of Network Systems, 7(2), 724-733. Lien externe
Lesage-Landry, A., Wang, H., Shames, I., Mancarella, P., & Taylor, J. (2020). Online convex optimization of multi-energy building-to-grid ancillary services. IEEE Transactions on Control Systems Technology, 28(6), 2416-2431. Lien externe
Lesage-Landry, A., Shames, I., & Taylor, J. A. (2020). Predictive online convex optimization. Automatica, 113, 108771 (9 pages). Lien externe
Lesage-Landry, A., & Taylor, J. A. (2020). A second-order cone model of transmission planning with alternating and direct current lines. European Journal of Operational Research, 281(1), 174-185. Lien externe
Lesage-Landry, A., & Taylor, J. A. (2018). The multi-armed bandit with stochastic plays. IEEE Transactions on Automatic Control, 63(7), 2280-2286. Lien externe
Lesage-Landry, A., & Taylor, J. A. (2018). Setpoint tracking with partially observed loads. IEEE Transactions on Power Systems, 33(5), 5615-5627. Lien externe
Lesage-Landry, A., & Taylor, J. A. (janvier 2017). Learning to shift thermostatically controlled loads [Communication écrite]. 5th Hawaii International Conference on System Science (HICSS 2017), Big Island, Hawaii. Lien externe
Lesage-Landry, A., & Taylor, J. A. (août 2017). Online convex optimization for demand response [Communication écrite]. IREP 2017 Symposium : X Bulk Power Systems Dynamics and Control Symposium (IREP 2017), Espinho, Portugal (8 pages). Non disponible
Loranger, S., Lesage-Landry, A., Soares De Lima Filho, E., Nemova, G., Dantas, N., Morais, P., & Kashyap, R. (février 2013). Spectroscopic and life-time measurements of quantum dot doped glass for optical refrigeration: a feasibility study [Communication écrite]. SPIE OPTO 2013, San Francisco, California (8 pages). Lien externe
Mai, V., Maisonneuve, P., Zhang, T., Nekoei, H., Paull, L., & Lesage-Landry, A. (2024). Correction to: Multi-agent reinforcement learning for fast-timescale demand response of residential loads. Machine Learning with Applications, 1 page. Lien externe
Maisonneuve, P., & Lesage-Landry, A. (2024). Learning-accelerated mixed-integer quadratic programming for unit commitment. (Rapport technique n° G-2024-08). Lien externe
Molénat, M., Mahseredjian, J., Rashidirad, N., & Lesage-Landry, A. (2024). On the frequency variation in load-flow calculations for islanded AC microgrid. (Rapport technique n° G-2024-26). Lien externe
Mai, V., Maisonneuve, P., Zhang, T., Nekoei, H., Paull, L., & Lesage-Landry, A. (2023). Multi-agent reinforcement learning for fast-timescale demand response of residential loads. Machine Learning with Applications, 32 pages. Lien externe
Mai, V., Zhang, T., & Lesage-Landry, A. (décembre 2021). Multi-agent reinforcement learning for renewable integration in the electric power grid [Communication écrite]. NeurIPS Workshop on Tackling Climate with Machine Learning. Non disponible
Mohamed, A., Lesage-Landry, A., & Taylor, J. A. (octobre 2017). Dispatching thermostatically controlled loads for frequency regulation using adversarial multi-armed bandits [Communication écrite]. IEEE Electrical Power and Energy Conference (EPEC 2017), Saskatoon, Sk (6 pages). Lien externe
Ouellette, O., Lesage-Landry, A., Scheffel, B., Hoogland, S., García de Arquer, F. P., & Sargent, E. H. (2020). Spatial collection in colloidal quantum dot solar cells. Advanced Functional Materials, 30(1), 1908200 (7 pages). Lien externe
Yahia, O. B., Garroussi, Z., Bélanger, O., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). Evolution of High-Throughput Satellite Systems: A Vision of Programmable Regenerative Payload. IEEE Communications Surveys & Tutorials, 3450292 (34 pages). Lien externe
