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ORCIDMatilde Gargiani
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2020 – today
- 2024
[j4]Matilde Gargiani
, Andrea Martinelli, Max Ruts Martinez, John Lygeros:
Parallel and Flexible Dynamic Programming via the Mini-Batch Bellman Operator. IEEE Trans. Autom. Control. 69(1): 455-462 (2024)- 2022
- [j3]Andrea Martinelli, Matilde Gargiani, John Lygeros:
Data-driven optimal control with a relaxed linear program. Autom. 136: 110052 (2022) - [j2]Matilde Gargiani, Andrea Zanelli, Dominic Liao-McPherson, Tyler H. Summers, John Lygeros:
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods. IEEE Control. Syst. Lett. 6: 2996-3001 (2022) - [j1]Andrea Martinelli, Matilde Gargiani, Marina Draskovic, John Lygeros:
Data-Driven Optimal Control of Affine Systems: A Linear Programming Perspective. IEEE Control. Syst. Lett. 6: 3092-3097 (2022) - [c5]Benjamin Gravell, Matilde Gargiani, John Lygeros, Tyler H. Summers:
Policy Iteration for Multiplicative Noise Output Feedback Control. CDC 2022: 2967-2972 - [c4]Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros:
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation. ICML 2022: 7223-7240 - [i8]Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros:
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation. CoRR abs/2202.00308 (2022) - [i7]Andrea Martinelli, Matilde Gargiani, Marina Draskovic, John Lygeros:
Data-driven optimal control of affine systems: A linear programming perspective. CoRR abs/2203.12044 (2022) - [i6]Benjamin Gravell, Matilde Gargiani, John Lygeros, Tyler H. Summers:
Policy Iteration for Multiplicative Noise Output Feedback Control. CoRR abs/2203.17165 (2022) - 2021
- [c3]Andrea Martinelli, Matilde Gargiani, John Lygeros:
On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control. CDC 2021: 4352-4357 - [i5]Andrea Martinelli, Matilde Gargiani, John Lygeros:
On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control. CoRR abs/2109.13193 (2021) - 2020
- [c2]Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter:
Transferring Optimality Across Data Distributions via Homotopy Methods. ICLR 2020 - [i4]Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter:
On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs. CoRR abs/2006.02409 (2020) - [i3]Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter:
Convergence Analysis of Homotopy-SGD for non-convex optimization. CoRR abs/2011.10298 (2020)
2010 – 2019
- 2019
- [i2]Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter:
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings. CoRR abs/1910.04522 (2019) - 2018
- [c1]Celestine Dünner, Aurélien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi:
A Distributed Second-Order Algorithm You Can Trust. ICML 2018: 1357-1365 - [i1]Celestine Dünner, Aurélien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi:
A Distributed Second-Order Algorithm You Can Trust. CoRR abs/1806.07569 (2018)
Coauthor Index
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