Difference between revisions of "Matthia Sabatelli"
GerdIsenberg (talk | contribs) (Created page with "'''Home * People * Matthia Sabatelli''' FILE:MatthiaSabatelli.jpg|border|right|thumb| Matthia Sabatelli <ref>[https://paintception.github.io/ Matthia Saba...") |
GerdIsenberg (talk | contribs) |
||
| Line 18: | Line 18: | ||
* [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2019'''). ''Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms''. [https://arxiv.org/abs/1909.01779 arXiv:1909.01779] | * [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2019'''). ''Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms''. [https://arxiv.org/abs/1909.01779 arXiv:1909.01779] | ||
==2020 ...== | ==2020 ...== | ||
| − | * [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2020'''). ''The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms''. | + | * [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2020'''). ''The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms''. [https://dblp.org/db/conf/ijcnn/ijcnn2020.html#SabatelliLGW20 IJCNN 2020] <ref>[https://github.com/paintception/Deep-Quality-Value-DQV-Learning- GitHub - paintception/Deep-Quality-Value-DQV-Learning-: DQV-Learning: a novel faster synchronous Deep Reinforcement Learning algorithm]</ref> |
* [[Matthia Sabatelli]], [https://scholar.google.com/citations?user=8-dz590AAAAJ&hl=en Mike Kestemont], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts] ('''2020'''). ''On the Transferability of Winning Tickets in Non-Natural Image Datasets''. [https://arxiv.org/abs/2005.05232 arXiv:2005.05232] | * [[Matthia Sabatelli]], [https://scholar.google.com/citations?user=8-dz590AAAAJ&hl=en Mike Kestemont], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts] ('''2020'''). ''On the Transferability of Winning Tickets in Non-Natural Image Datasets''. [https://arxiv.org/abs/2005.05232 arXiv:2005.05232] | ||
Revision as of 08:39, 27 May 2021
Home * People * Matthia Sabatelli
Matthia Sabatelli [1]
Matthia Sabatelli,
an Italian computer scientist and Ph.D. candidate at University of Liège,
researching on transfer learning which bridges between supervised and deep reinforcement learning.
He holds a B.Sc. from University of Trento in 2014, and a M.Sc. from University of Groningen in 2017 [2].
In his M.Sc thesis Matthia Sabatelli elaborates on learning to play chess with minimal lookahead, using multilayer perceptrons versus convolutional neural networks to approximate Stockfish’s evaluation, also comparing two different board representations for the input layer
[3].
Selected Publications
2017 ...
- Matthia Sabatelli (2017). Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks. Master's thesis, University of Groningen, pdf [5]
- Matthia Sabatelli, Francesco Bidoia, Valeriu Codreanu, Marco Wiering (2018). Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead. ICPRAM 2018, pdf
- Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco Wiering (2018). Deep Quality-Value (DQV) Learning. arXiv:1810.00368
- Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco Wiering (2019). Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms. arXiv:1909.01779
2020 ...
- Matthia Sabatelli, Gilles Louppe, Pierre Geurts, Marco Wiering (2020). The Deep Quality-Value Family of Deep Reinforcement Learning Algorithms. IJCNN 2020 [6]
- Matthia Sabatelli, Mike Kestemont, Pierre Geurts (2020). On the Transferability of Winning Tickets in Non-Natural Image Datasets. arXiv:2005.05232
External Links
- Matthia Sabatelli | LinkedIn
- Matthia Sabatelli
- Matthia Sabatelli - Google Scholar
- paintception (Matthia Sabatelli) · GitHub
References
- ↑ Matthia Sabatelli
- ↑ Matthia Sabatelli | LinkedIn
- ↑ Matthia Sabatelli (2017). Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks. Master's thesis, University of Groningen, pdf
- ↑ dblp: Matthia Sabatelli
- ↑ GitHub - paintception/DeepChess
- ↑ GitHub - paintception/Deep-Quality-Value-DQV-Learning-: DQV-Learning: a novel faster synchronous Deep Reinforcement Learning algorithm
