Simone Totaro

According to our database, Simone Totaro authored at least 11 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Hierarchical Representation Learning for Markov Decision Processes.

Lorenzo Steccanella, Simone Totaro, Anders Jonsson

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

A general class of surrogate functions for stable and efficient reinforcement learning.

Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Müller, Shivam Garg, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A functional mirror ascent view of policy gradient methods with function approximation.

Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro, Nicolas Le Roux

CoRR, 2021

SQL Injections and Reinforcement Learning: An Empirical Evaluation of the Role of Action Structure.

Manuel Del Verme, Åvald Åslaugson Sommervoll, László Erdödi, Simone Totaro, Fabio Massimo Zennaro

Proceedings of the Secure IT Systems - 26th Nordic Conference, NordSec 2021, Virtual Event, 2021

Fast Stochastic Kalman Gradient Descent for Reinforcement Learning.

Simone Totaro, Anders Jonsson

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

2020

Adaptive Smoothing for Path Integral Control.

Dominik Thalmeier, Hilbert J. Kappen, Simone Totaro, Vicenç Gómez

J. Mach. Learn. Res., 2020

A non-parametric softmax for improving neural attention in time-series forecasting.

Simone Totaro, Amir Hussain, Simone Scardapane

Neurocomputing, 2020

Hierarchical reinforcement learning for efficient exploration and transfer.

Lorenzo Steccanella, Simone Totaro, Damien Allonsius, Anders Jonsson

CoRR, 2020

Lifelong Control of Off-grid Microgrid with Model Based Reinforcement Learning.

Simone Totaro, Ioannis Boukas, Anders Jonsson, Bertrand Cornélusse

CoRR, 2020

2019

Kafnets: Kernel-based non-parametric activation functions for neural networks.

Simone Scardapane, Steven Van Vaerenbergh, Simone Totaro, Aurelio Uncini

Neural Networks, 2019

2018

Recurrent Neural Networks with flexible Gates using Kernel activation Functions.

Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello, Simone Totaro, Aurelio Uncini

Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018