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Matilde Gargiani
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A distributed second-order algorithm you can trust
C Dünner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
International Conference on Machine Learning, 1358-1366, 2018
352018
On the promise of the stochastic generalized Gauss-Newton method for training DNNs
M Gargiani, A Zanelli, M Diehl, F Hutter
arXiv preprint arXiv:2006.02409, 2020
212020
Data-driven optimal control with a relaxed linear program
A Martinelli, M Gargiani, J Lygeros
Automatica 2022, 2020
172020
Data-driven optimal control of affine systems: A linear programming perspective
A Martinelli, M Gargiani, M Draskovic, J Lygeros
IEEE Control Systems Letters, 2022
152022
PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation
M Gargiani, A Zanelli, A Martinelli, T Summers, J Lygeros
ICML 2022, 2022
152022
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings
M Gargiani, A Klein, S Falkner, F Hutter
ICML 2018 (Workshop on AutoML), 2019
112019
Hyperparameter optimization
A Biedenkapp, K Eggensperger, T Elsken, S Falkner, M Feurer, ...
Artificial Intelligence 1, 35, 2018
82018
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods
M Gargiani, A Zanelli, D Liao-McPherson, T Summers, J Lygeros
IEEE Control Systems Letters 6, 2022
62022
Policy Iteration for Multiplicative Noise Output Feedback Control
B Gravell, M Gargiani, J Lygeros, TH Summers
CDC 2022, 2022
42022
Hessian-CoCoA: a general parallel and distributed framework for non-strongly convex regularizers
M Gargiani
ETH Zurich, 2017
42017
Parallel and Flexible Dynamic Programming Via the Mini-Batch Bellman Operator
M Gargiani, A Martinelli, MR Martinez, J Lygeros
IEEE Transactions on Automatic Control 69 (1), 455-462, 2023
32023
Dynamic Programming Through the Lens of Semismooth Newton-Type Methods (Extended Version)
M Gargiani, A Zanelli, D Liao Mc-Pherson, T Summers, J Lygeros
https://arxiv.org/abs/2203.08678, 2022
32022
Parallel and Flexible Dynamic Programming via the Randomized Mini-Batch Operator
M Gargiani, A Martinelli, M R. Martinez, J Lygeros
arXiv preprint arXiv:2110.02901, 2021
32021
On the Synthesis of Bellman Inequalities for Data-Driven Optimal Control
A Martinelli, M Gargiani, J Lygeros
CDC 2021, 2021
32021
Convergence Analysis of Homotopy-SGD for Non-Convex Optimization
M Gargiani, A Zanelli, Q Tran-Dinh, M Diehl, F Hutter
arXiv preprint arXiv:2011.10298, 2020
32020
Transferring Optimality Across Data Distributions via Homotopy Methods
M Gargiani, A Zanelli, Q Tran-Dinh, M Diehl, F Hutter
ICLR 2020, 2020
22020
Inexact GMRES Policy Iteration for Large-Scale Markov Decision Processes
M Gargiani, D Liao-McPherson, A Zanelli, J Lygeros
12022
Inexact Policy Iteration Methods for Large-Scale Markov Decision Processes
M Gargiani, R Sieber, E Balta, D Liao-McPherson, J Lygeros
https://arxiv.org/abs/2404.06136, 2024
2024
Method, device and computer program for predicting a learning curve
M Gargiani, A Klein, F Hutter
https://patents.google.com/patent/DE102019207911A1/en, 2023
2023
Method for training a neural network
B Wilhelm, F Hutter, M Gargiani
US Patent App. 17/657,403, 2022
2022
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