Stefano Sarao Mannelli | DeepAI

DeepAI AI Chat

Featured Co-authors

Florent Krzakala
88 publications
Lenka Zdeborová
80 publications
Negar Rostamzadeh
29 publications
Eric Vanden-Eijnden
22 publications
Argyris Kalogeratos
21 publications
Giulio Biroli
21 publications
Sebastian Goldt
19 publications
Alessandro Laio
16 publications
Marc Mézard
14 publications
Luca Saglietti
13 publications
Claudia Clopath
12 publications

∙ 06/17/2023

The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions

Reinforcement learning (RL) algorithms have proven transformative in a r...

0 Nishil Patel, et al. ∙

∙ 03/02/2023

Optimal transfer protocol by incremental layer defrosting

Transfer learning is a powerful tool enabling model training with limite...

0 Federica Gerace, et al. ∙

∙ 05/31/2022

Inducing bias is simpler than you think

Machine learning may be oblivious to human bias but it is not immune to ...

0 Stefano Sarao Mannelli, et al. ∙

∙ 05/18/2022

Maslow's Hammer for Catastrophic Forgetting: Node Re-Use vs Node Activation

Continual learning - learning new tasks in sequence while maintaining pe...

0 Sebastian Lee, et al. ∙

∙ 06/15/2021

An Analytical Theory of Curriculum Learning in Teacher-Student Networks

In humans and animals, curriculum learning – presenting data in a curate...

11 Luca Saglietti, et al. ∙

∙ 06/09/2021

Probing transfer learning with a model of synthetic correlated datasets

Transfer learning can significantly improve the sample efficiency of neu...

0 Federica Gerace, et al. ∙

∙ 02/23/2021

Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problem

When optimizing over loss functions it is common practice to use momentu...

0 Stefano Sarao Mannelli, et al. ∙

∙ 09/20/2020

Epidemic mitigation by statistical inference from contact tracing data

Contact-tracing is an essential tool in order to mitigate the impact of ...

4 Antoine Baker, et al. ∙

∙ 06/27/2020

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

We study the dynamics of optimization and the generalization properties ...

7 Stefano Sarao Mannelli, et al. ∙

∙ 06/24/2020

Winning the competition: enhancing counter-contagion in SIS-like epidemic processes

In this paper we consider the epidemic competition between two generic d...

0 Argyris Kalogeratos, et al. ∙

∙ 06/12/2020

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval

Despite the widespread use of gradient-based algorithms for optimizing h...

0 Stefano Sarao Mannelli, et al. ∙

∙ 01/02/2020

Thresholds of descending algorithms in inference problems

We review recent works on analyzing the dynamics of gradient-based algor...

27 Stefano Sarao Mannelli, et al. ∙

∙ 07/18/2019

Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model

Gradient-based algorithms are effective for many machine learning tasks,...

1 Stefano Sarao Mannelli, et al. ∙

∙ 02/01/2019

Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model

In this work we analyse quantitatively the interplay between the loss la...

28 Stefano Sarao Mannelli, et al. ∙

∙ 12/21/2018

Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference

Gradient-descent-based algorithms and their stochastic versions have wid...

20 Stefano Sarao Mannelli, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world