Stefano Sarao Mannelli

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

High Dimensions

Top Venues

Mach. Learn. Sci. Technol.

Publications

Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. CoRR (2024)
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 (2024)
Nishil Patel, Sebastian Lee, Stefano Sarao Mannelli, Sebastian Goldt, Adrew Saxe
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions. CoRR (2023)
Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio
Optimal transfer protocol by incremental layer defrosting. CoRR (2023)
Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. NeurIPS (2022)
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) (2022)
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 (2022)
Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti
Inducing bias is simpler than you think. CoRR (2022)
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)
Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe
An Analytical Theory of Curriculum Learning in Teacher-Student Networks. CoRR (2021)
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová
Probing transfer learning with a model of synthetic correlated datasets. CoRR (2021)
Stefano Sarao Mannelli, Pierfrancesco Urbani
Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problem. CoRR (2021)
Stefano Sarao Mannelli, Pierfrancesco Urbani
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems. NeurIPS (2021)
Argyris Kalogeratos, Stefano Sarao Mannelli
Winning the competition: enhancing counter-contagion in SIS-like epidemic processes. CoRR (2020)
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 (2020)
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)
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. NeurIPS (2020)
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 (2020)
Levent Sagun, Çaglar Gülçehre, Adriana Romero, Negar Rostemzadeh, Stefano Sarao Mannelli
Post-Workshop Report on Science meets Engineering in Deep Learning, NeurIPS 2019, Vancouver. CoRR (2020)
Stefano Sarao Mannelli, Lenka Zdeborová
Thresholds of descending algorithms in inference problems. CoRR (2020)
Stefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions. CoRR (2020)
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)
Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model. CoRR (2019)
Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models. ICML (2019)
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 (2019)
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 (2018)