Matilde Gargiani
Title
Cited by
Cited by
Year
A distributed second-order algorithm you can trust
C DŁnner, A Lucchi, M Gargiani, A Bian, T Hofmann, M Jaggi
International Conference on Machine Learning, 1358-1366, 2018
232018
Hyperparameter optimization
A Biedenkapp, K Eggensperger, T Elsken, S Falkner, M Feurer, ...
Artificial Intelligence 1, 35, 2018
62018
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
42020
Hessian-CoCoA: a general parallel and distributed framework for non-strongly convex regularizers
M Gargiani
ETH Zurich, 2017
42017
Probabilistic Rollouts for Learning Curve Extrapolation Across Hyperparameter Settings
M Gargiani, A Klein, S Falkner, F Hutter
ICML 2018 (Workshop on AutoML), 2019
22019
Transferring Optimality Across Data Distributions via Homotopy Methods
M Gargiani, A Zanelli, Q Tran-Dinh, M Diehl, F Hutter
ICLR, 2020
12020
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
2020
Data-driven optimal control with a relaxed linear program
A Martinelli, M Gargiani, J Lygeros
arXiv preprint arXiv:2003.08721, 2020
2020
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Articles 1–8