Matilde Gargiani

According to our database, Matilde Gargiani authored at least 16 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Inside madupite: Technical Design and Performance.

Matilde Gargiani, Robin Sieber, Philip Pawlowsky, John Lygeros

CoRR, July, 2025

madupite: A High-Performance Distributed Solver for Large-Scale Markov Decision Processes.

Matilde Gargiani, Philip Pawlowsky, Robin Sieber, Václav Hapla, John Lygeros

J. Open Source Softw., May, 2025

madupite: A High-Performance Distributed Solver for Large-Scale Markov Decision Processes.

Matilde Gargiani, Philip Pawlowsky, Robin Sieber, Vaclav Hapla, John Lygeros

Dataset, March, 2025

madupite.

Matilde Gargiani, Philip Pawlowsky, Robin Sieber, Vaclav Hapla, John Lygeros

Dataset, February, 2025

2024

Parallel and Flexible Dynamic Programming via the Mini-Batch Bellman Operator.

Matilde Gargiani, Andrea Martinelli, Max Ruts Martinez, John Lygeros

IEEE Trans. Autom. Control., January, 2024

2022

Data-Driven Optimal Control of Affine Systems: A Linear Programming Perspective.

Andrea Martinelli, Matilde Gargiani, Marina Draskovic, John Lygeros

IEEE Control. Syst. Lett., 2022

Dynamic Programming Through the Lens of Semismooth Newton-Type Methods.

Matilde Gargiani, Andrea Zanelli, Dominic Liao-McPherson, Tyler H. Summers, John Lygeros

IEEE Control. Syst. Lett., 2022

Data-driven optimal control with a relaxed linear program.

Andrea Martinelli, Matilde Gargiani, John Lygeros

Autom., 2022

PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation.

Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros

Proceedings of the International Conference on Machine Learning, 2022

Policy Iteration for Multiplicative Noise Output Feedback Control.

Benjamin Gravell, Matilde Gargiani, John Lygeros, Tyler H. Summers

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021

On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control.

Andrea Martinelli, Matilde Gargiani, John Lygeros

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Convergence Analysis of Homotopy-SGD for non-convex optimization.

Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter

CoRR, 2020

On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs.

Matilde Gargiani, Andrea Zanelli, Moritz Diehl, Frank Hutter

CoRR, 2020

Transferring Optimality Across Data Distributions via Homotopy Methods.

Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh, Moritz Diehl, Frank Hutter

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings.

Matilde Gargiani, Aaron Klein, Stefan Falkner, Frank Hutter

CoRR, 2019

2018

A Distributed Second-Order Algorithm You Can Trust.

Celestine Dünner, Aurélien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi

Proceedings of the 35th International Conference on Machine Learning, 2018