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ORCIDStefano Sarao Mannelli
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2020 – today
- 2024
[c9]Jin Hwa Lee, Stefano Sarao Mannelli, Andrew M. Saxe:
Why Do Animals Need Shaping? A Theory of Task Composition and Curriculum Learning. ICML 2024- [c8]Stefano Sarao Mannelli, Yaraslau Ivashinka, Andrew M. Saxe, Luca Saglietti:
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks. ICML 2024 - [i19]Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli:
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. CoRR abs/2405.18296 (2024) - [i18]Stefano Sarao Mannelli, Yaraslau Ivashinka, Andrew M. Saxe, Luca Saglietti:
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks. CoRR abs/2406.01589 (2024) - [i17]Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco:
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory. CoRR abs/2409.18061 (2024) - 2023
- [i16]Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio:
Optimal transfer protocol by incremental layer defrosting. CoRR abs/2303.01429 (2023) - [i15]Nishil Patel, Sebastian Lee, Stefano Sarao Mannelli, Sebastian Goldt, Andrew M. Saxe:
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions. CoRR abs/2306.10404 (2023) - 2022
- [j1]Federica Gerace
, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová:
Probing transfer learning with a model of synthetic correlated datasets. Mach. Learn. Sci. Technol. 3(1): 15030 (2022) - [c7]Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt, Andrew M. Saxe:
Maslow's Hammer in Catastrophic Forgetting: Node Re-Use vs. Node Activation. ICML 2022: 12455-12477 - [c6]Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe:
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. NeurIPS 2022 - [i14]Sebastian Lee, Stefano Sarao Mannelli, Claudia Clopath, Sebastian Goldt, Andrew M. Saxe:
Maslow's Hammer for Catastrophic Forgetting: Node Re-Use vs Node Activation. CoRR abs/2205.09029 (2022) - [i13]Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti:
Inducing bias is simpler than you think. CoRR abs/2205.15935 (2022) - 2021
- [c5]Stefano Sarao Mannelli, Pierfrancesco Urbani:
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems. NeurIPS 2021: 187-199 - [i12]Stefano Sarao Mannelli, Pierfrancesco Urbani:
Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problem. CoRR abs/2102.11755 (2021) - [i11]Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová:
Probing transfer learning with a model of synthetic correlated datasets. CoRR abs/2106.05418 (2021) - [i10]Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe:
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. CoRR abs/2106.08068 (2021) - 2020
- [c4]Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová:
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. NeurIPS 2020 - [c3]Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová:
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. NeurIPS 2020 - [i9]Stefano Sarao Mannelli, Lenka Zdeborová:
Thresholds of descending algorithms in inference problems. CoRR abs/2001.00479 (2020) - [i8]Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová:
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval. CoRR abs/2006.06997 (2020) - [i7]Argyris Kalogeratos, Stefano Sarao Mannelli:
Winning the competition: enhancing counter-contagion in SIS-like epidemic processes. CoRR abs/2006.13395 (2020) - [i6]Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová:
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. CoRR abs/2006.15459 (2020) - [i5]Levent Sagun, Çaglar Gülçehre, Adriana Romero, Negar Rostamzadeh, Stefano Sarao Mannelli:
Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver. CoRR abs/2007.13483 (2020) - [i4]Antoine Baker, Indaco Biazzo, Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta, Alessandro Ingrosso, Florent Krzakala, Fabio Mazza, Marc Mézard, Anna Paola Muntoni, Maria Refinetti, Stefano Sarao Mannelli, Lenka Zdeborová:
Epidemic mitigation by statistical inference from contact tracing data. CoRR abs/2009.09422 (2020)
2010 – 2019
- 2019
- [c2]Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová:
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. ICML 2019: 4333-4342 - [c1]Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová:
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models. NeurIPS 2019: 8676-8686 - [i3]Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová:
Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model. CoRR abs/1902.00139 (2019) - [i2]Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Lenka Zdeborová:
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model. CoRR abs/1907.08226 (2019) - 2018
- [i1]Stefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová:
Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference. CoRR abs/1812.09066 (2018)
Coauthor Index
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last updated on 2024-10-18 19:33 CEST by the dblp team
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