Matthia Sabatelli

According to our database, Matthia Sabatelli authored at least 25 papers between 2014 and 2024.

Collaborative distances:

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

2024

VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts.

Marius Captari, Remo Sasso, Matthia Sabatelli

CoRR, 2024

Mapping Transformer Leveraged Embeddings for Cross-Lingual Document Representation.

Tsegaye Misikir Tashu, Eduard-Raul Kontos, Matthia Sabatelli, Matias Valdenegro-Toro

CoRR, 2024

Contextual Online Imitation Learning (COIL): Using Guide Policies in Reinforcement Learning.

Alexander Hill, Marc Groefsema, Matthia Sabatelli, Raffaella Carloni, Marco Grzegorczyk

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning.

Remo Sasso, Matthia Sabatelli, Marco A. Wiering

Trans. Mach. Learn. Res., 2023

Learning Perceptive Bipedal Locomotion over Irregular Terrain.

Bart van Marum, Matthia Sabatelli, Hamidreza Kasaei

CoRR, 2023

Bridging the Reality Gap of Reinforcement Learning based Traffic Signal Control using Domain Randomization and Meta Learning.

Arthur Müller, Matthia Sabatelli

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

2022

Contributions to Deep Transfer Learning: from Supervised to Reinforcement Learning.

Matthia Sabatelli

PhD thesis, 2022

Factors of Influence of the Overestimation Bias of Q-Learning.

Julius Wagenbach, Matthia Sabatelli

CoRR, 2022

Machine Learning Students Overfit to Overfitting.

Matias Valdenegro-Toro, Matthia Sabatelli

Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022

Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Masking.

Arthur Müller, Matthia Sabatelli

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

How Well Do Vision Transformers (VTs) Transfer to the Non-natural Image Domain? An Empirical Study Involving Art Classification.

Vincent Tonkes, Matthia Sabatelli

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

2021

Advances in Digital Music Iconography: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain.

Matthia Sabatelli, Nikolay Banar, Marie Cocriamont, Eva Coudyzer, Karine Lasaracina, Walter Daelemans, Pierre Geurts, Mike Kestemont

Digit. Humanit. Q., 2021

On The Transferability of Deep-Q Networks.

Matthia Sabatelli, Pierre Geurts

CoRR, 2021

Fractional Transfer Learning for Deep Model-Based Reinforcement Learning.

Remo Sasso, Matthia Sabatelli, Marco A. Wiering

CoRR, 2021

On the Transferability of Winning Tickets in Non-natural Image Datasets.

Matthia Sabatelli, Mike Kestemont, Pierre Geurts

Proceedings of the 16th International Joint Conference on Computer Vision, 2021

Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain.

Nikolay Banar, Matthia Sabatelli, Pierre Geurts, Walter Daelemans, Mike Kestemont

Proceedings of the Computer Vision and Image Analysis of Art 2021, 2021

2020

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning.

Pascal Leroy, Damien Ernst, Pierre Geurts, Gilles Louppe, Jonathan Pisane, Matthia Sabatelli

CoRR, 2020

The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms.

Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Forest Fire Control with Learning from Demonstration and Reinforcement Learning.

Travis Hammond, Dirk Jelle Schaap, Matthia Sabatelli, Marco A. Wiering

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms.

Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering

CoRR, 2019

Deep Quality-Value (DQV) Learning.

Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco A. Wiering

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead.

Matthia Sabatelli, Francesco Bidoia, Valeriu Codreanu, Marco A. Wiering

Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, 2018

A Deep Convolutional Neural Network for Location Recognition and Geometry based Information.

Francesco Bidoia, Matthia Sabatelli, Amirhossein Shantia, Marco A. Wiering, Lambert Schomaker

Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, 2018

Deep Transfer Learning for Art Classification Problems.

Matthia Sabatelli, Mike Kestemont, Walter Daelemans, Pierre Geurts

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2014

Correlation of significant places with self-reported state of bipolar disorder patients.

Matthia Sabatelli, Venet Osmani, Oscar Mayora, Agnes Grünerbl, Paul Lukowicz

Proceedings of the 4th International Conference on Wireless Mobile Communication and Healthcare: "Transforming healthcare through innovations in mobile and wireless technologies", 2014