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Documents dont l'auteur est "Lesage-Landry, Antoine"

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Nombre de documents: 64

A

Almekhlafi, M., Lesage-Landry, A., & Karabulut Kurt, G. (2025). Access Inequality in LEO Satellite Networks: A Case Study of High-Latitude Coverage in Northern Québec. IEEE Open Journal of Vehicular Technology, 6, 1613-1630. Disponible

Audet, X., Qako, K., & Lesage-Landry, A. (2025). A distributionally robust optimization strategy for virtual bidding in two-settlement electricity markets. (Rapport technique n° G-2025-31). Lien externe

Audet, X., Qako, K., & Lesage-Landry, A. (2025). A Distributionally Robust Optimization Strategy for Virtual Bidding in Two-Settlement Electricity Markets. Sustainable Energy, Grids and Networks, 101904. Lien externe

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Ben Yahia, O., Garroussi, Z., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). A scalable architecture for future regenerative satellite payloads. (Rapport technique n° G-2024-40). Lien externe

Ben Yahia, O., Garroussi, Z., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2024). A Scalable Architecture for Future Regenerative Satellite Payloads. IEEE Wireless Communications Letters, 1-1. Lien externe

Ben Yahia, O., 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

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

Ben Yahia, O., Garroussi, Z., Bélanger, O., Sanso, B., Frigon, J.-F., Martel, S., Lesage-Landry, A., & Karabulut Kurt, G. (2023). Evolution of high throughput satellite systems: Vision, requirements, and key technologies. (Rapport technique n° G-2023-44). Lien externe

C

Coulombe, M., Berger, M., & Lesage-Landry, A. (2025). Simulation of a closed-loop dc-dc converter using a physics-informed neural network-based model. Electric Power Systems Research, 252, 112408 (8 pages). Lien externe

Coulombe, M.-A., Berger, M., & Lesage-Landry, A. (2025). Simulation of a closed-loop dc-dc converter using a physics-informed neural network-based model. (Rapport technique n° G-2025-41). Lien externe

D

Durette, J., Karabulut Kurt, G., & Lesage-Landry, A. (2025). Task mapping strategies for electric power system simulations on heterogeneous clusters. (Rapport technique n° G-2025-32). Lien externe

Durette, J., Karabulut Kurt, G., & Lesage-Landry, A. (septembre 2025). Task Mapping Strategies for Electric Power System Simulations on Heterogeneous Clusters [Communication écrite]. International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm 2025), North York, ON, Canada. 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

F

Farzin, A. A., Pun, Y.-M., Lesage-Landry, A., Diouane, Y., & Shames, I. (2025). Min-max optimisation for nonconvex-nonconcave functions using a random zeroth-order extragradient algorithm. Transactions on Machine Learning Research, 59 pages. Disponible

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Garroussi, Z., Ben Yahia, O., Sanso, B., Frigon, J.-F., Martel, S., Mantelet, G., Lesage-Landry, A., & Karabulut Kurt, G. (juin 2025). Multi-Priority Scheduling for Traffic Management in Future Scalable Payloads [Communication écrite]. IEEE International Conference on Communications Workshops (ICC Workshops 2025), Montreal, QC, Canada. Lien externe

H

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

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Kim, J., Mahseredjian, J., Karaagac, U., Lesage-Landry, A., Grilo, A. P., & Kim, C.-H. (novembre 2024). State-Space Models for Control Interaction Analysis of DFIG and FSC Wind Parks [Communication écrite]. 50th Annual Conference of the IEEE Industrial Electronics Society (IECON 2024), Chicago, IL, USA. Lien externe

L

Le Digabel, S., Lesage-Landry, A., Salomon, L., & Tribes, C. (2025). Efficient search strategies for constrained multiobjective blackbox optimization. (Rapport technique n° G-2025-28). 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

Lupien, J.-L., Shames, I., & Lesage-Landry, A. (2024). Online Interior-Point Methods for Time-Varying Equality-Constrained Optimization. IEEE Transactions on Automatic Control, 8 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

Li, F., Kocar, I., & Lesage-Landry, A. (2023). Mitigating equipment overloads due to electric vehicle charging using customer incentives. (Rapport technique n° G-2023-01). Lien externe

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

Lupien, J.-L., & Lesage-Landry, A. (2022). Online Newton's method with linear time-varying equality constraints. (Rapport technique n° G-2022-49). Lien externe

Lesage-Landry, A., Pellerin, F., Taylor, J. A., & Callaway, D. (2022). Optimally scheduling public safety power shutoffs. (Rapport technique n° G-2022-09). 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). Approximated multi-agent fitted Q iteration. (Rapport technique n° G-2022-02). Lien externe

Lesage-Landry, A., & Callaway, D. S. (2022). Batch reinforcement learning for network-safe demand response in unknown electric grids. (Rapport technique n° G-2021-55). 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

M

Molénat, M. C., Mahseredjian, J., Rashidirad, N., & Lesage-Landry, A. (2025). On the frequency variation in load-flow calculations for islanded alternating current microgrids. Mathematics and Computers in Simulation. Présentée à International Conference on Modeling and Simulation of Electric Machines, Converters and Systems (ElectrIMACS 2024), Castelló, Spain. 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

Merrigan, H., Yu-Hsin, W., Shigematsu, K., Yamamoto, M., Imaoka, J., & Lesage-Landry, A. (novembre 2024). Optimising Electric Vehicle Wireless Charging Systems Using Neural Networks to Enable Free-Position Parking [Communication écrite]. 13th International Conference on Renewable Energy Research and Applications (ICRERA 2024), Nagasaki, Japan. 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

N

N'Zi, K., Rashidirad, N., Mahseredjian, J., & Lesage-Landry, A. (octobre 2025). Modified and Augmented Nodal Analysis-based Optimal Power Flow [Communication écrite]. 51st Annual Conference of the IEEE Industrial Electronics Society (IECON 2025), Madrid, Spain (6 pages). Lien externe

O

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

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Pallage, J., & Lesage-Landry, A. (2025). Wasserstein Distributionally Robust Shallow Convex Neural Networks. INFORMS Journal on Optimization. Lien externe

Paré, M.-C., Dermardiros, V., & Lesage-Landry, A. (octobre 2025). Efficient Data-Driven Model Predictive Control for Demand Response of Commercial Buildings [Communication écrite]. 51st Annual Conference of the IEEE Industrial Electronics Society (IECON 2025), Madrid, Spain (8 pages). Lien externe

Pallage, J., & Lesage-Landry, A. (2024). (Trustworthy) AI for Québec's virtual power plant. (Rapport technique n° G-2024-23). Lien externe

R

Ricaux, V., Legrain, A., & Lesage-Landry, A. (2024). On the clique decomposition impact to the optimal power flow semidefinite relaxation solve time. (Rapport technique n° G-2024-77). Lien externe

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Soldati, C., Le Digabel, S., & Lesage-Landry, A. (2025). Blackbox optimization for loss minimization in power distribution networks using feeder reconfiguration. (Rapport technique n° G-2025-52). Lien externe

X

Xue, T., Zhao, M., Kocar, I., Ghafouri, M., Lesage-Landry, A., Bu, S., & Zhu, Z. (2025). Efficient Deep Reinforcement Learning-Based Supplementary Damping Control with a Coordinated RMS Training and EMT Testing Scheme. IEEE Transactions on Power Delivery, 1-14. Lien externe

Liste produite: Fri Dec 5 04:48:30 2025 EST.