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ORCIDFrançois Pacaud
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2020 – today
- 2024
[j4]François Pacaud
, Sungho Shin, Michel Schanen, Daniel Adrian Maldonado, Mihai Anitescu:
Accelerating Condensed Interior-Point Methods on SIMD/GPU Architectures. J. Optim. Theory Appl. 202(1): 184-203 (2024)- 2023
- [c4]Sungho Shin, François Pacaud, Emil Contantinescu, Mihai Anitescu:
Constrained Policy Optimization for Stochastic Optimal Control under Nonstationary Uncertainties*. ACC 2023: 634-639 - [c3]David L. Cole, Sungho Shin, François Pacaud, Victor M. Zavala, Mihai Anitescu:
Exploiting GPU/SIMD Architectures for Solving Linear-Quadratic MPC Problems*. ACC 2023: 3995-4000 - [i4]Sungho Shin, François Pacaud, Mihai Anitescu:
Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods. CoRR abs/2307.16830 (2023) - 2022
- [c2]François Pacaud, Michel Schanen, Daniel Adrian Maldonado, Alexis Montoison, Valentin Churavy, Julian Samaroo, Mihai Anitescu:
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods. PP 2022: 60-71 - [i3]François Pacaud, Michel Schanen, Daniel Adrian Maldonado, Alexis Montoison, Valentin Churavy, Julian Samaroo, Mihai Anitescu:
Batched Second-Order Adjoint Sensitivity for Reduced Space Methods. CoRR abs/2201.00241 (2022) - [i2]Alexander Engelmann, Sungho Shin, François Pacaud, Victor M. Zavala:
Scalable Primal Decomposition Schemes for Large-Scale Infrastructure Networks. CoRR abs/2212.11571 (2022) - 2021
- [c1]Daniel Adrian Maldonado, Michel Schanen, François Pacaud, Mihai Anitescu:
Domain Decomposition Preconditioners for Unstructured Network Problems in Parallel Vector Architectures. ICPP Workshops 2021: 30:1-30:5 - [i1]Youngdae Kim, François Pacaud, Kibaek Kim, Mihai Anitescu:
Leveraging GPU batching for scalable nonlinear programming through massive Lagrangian decomposition. CoRR abs/2106.14995 (2021) - 2020
- [j3]Pierre Carpentier, Jean-Philippe Chancelier, Michel De Lara, François Pacaud:
Mixed Spatial and Temporal Decompositions for Large-Scale Multistage Stochastic Optimization Problems. J. Optim. Theory Appl. 186(3): 985-1005 (2020) - [j2]Vincent Leclère, Pierre Carpentier, Jean-Philippe Chancelier, Arnaud Lenoir, François Pacaud:
Exact Converging Bounds for Stochastic Dual Dynamic Programming via Fenchel Duality. SIAM J. Optim. 30(2): 1223-1250 (2020)
2010 – 2019
- 2018
- [j1]Pierre Carpentier, Jean-Philippe Chancelier, Vincent Leclère, François Pacaud:
Stochastic decomposition applied to large-scale hydro valleys management. Eur. J. Oper. Res. 270(3): 1086-1098 (2018)
Coauthor Index
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