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Created page with "'''Home * People * Matthia Sabatelli''' FILE:MatthiaSabatelli.jpg|border|right|thumb| Matthia Sabatelli <ref>[https://paintception.github.io/ Matthia Saba..."
'''[[Main Page|Home]] * [[People]] * Matthia Sabatelli'''
[[FILE:MatthiaSabatelli.jpg|border|right|thumb| Matthia Sabatelli <ref>[https://paintception.github.io/ Matthia Sabatelli]</ref> ]]
'''Matthia Sabatelli''',<br/>
an Italian computer scientist and Ph.D. candidate at [https://en.wikipedia.org/wiki/University_of_Li%C3%A8ge University of Liège],
researching on [https://en.wikipedia.org/wiki/Transfer_learning transfer learning] which bridges between [[Supervised Learning|supervised]] and [[Deep Learning|deep]] [[Reinforcement Learning|reinforcement learning]].
He holds a B.Sc. from [https://en.wikipedia.org/wiki/University_of_Trento University of Trento] in 2014, and a M.Sc. from [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen] in 2017 <ref>[https://www.linkedin.com/in/matthia-sabatelli-70370b93/ Matthia Sabatelli | LinkedIn]</ref>.
In his M.Sc thesis Matthia Sabatelli elaborates on [[Learning|learning]] to play chess with minimal [[Search|lookahead]], using [[Neural Networks#Deep|multilayer perceptrons]] versus [[Neural Networks#Convolutional|convolutional neural networks]] to approximate [[Stockfish|Stockfish’s]] [[Evaluation|evaluation]], also comparing two different [[Board Representation|board representations]] for the input layer
<ref>[[Matthia Sabatelli]] ('''2017'''). ''Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks''. Master's thesis, [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen], [https://www.ai.rug.nl/~mwiering/Thesis_Matthia_Sabatelli.pdf pdf]</ref>.
=Selected Publications=
<ref>[https://dblp.org/pid/160/6434.html dblp: Matthia Sabatelli]</ref>
==2017 ...==
* [[Matthia Sabatelli]] ('''2017'''). ''Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks''. Master's thesis, [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen], [https://www.ai.rug.nl/~mwiering/Thesis_Matthia_Sabatelli.pdf pdf] <ref>[https://github.com/paintception/DeepChess GitHub - paintception/DeepChess]</ref>
* [[Matthia Sabatelli]], [[Francesco Bidoia]], [[Valeriu Codreanu]], [[Marco Wiering]] ('''2018'''). ''Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead''. ICPRAM 2018, [https://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/ICPRAM_CHESS_DNN_2018.pdf pdf]
* [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2018'''). ''Deep Quality-Value (DQV) Learning''. [https://arxiv.org/abs/1810.00368 arXiv:1810.00368]
* [[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 ...==
* [[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://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]
=External Links=
* [https://www.linkedin.com/in/matthia-sabatelli-70370b93/ Matthia Sabatelli | LinkedIn]
* [https://paintception.github.io/ Matthia Sabatelli]
* [https://scholar.google.com/citations?user=YO2Php8AAAAJ&hl=en Matthia Sabatelli - Google Scholar]
* [https://github.com/paintception paintception (Matthia Sabatelli) · GitHub]
=References=
<references />
'''[[People|Up one Level]]'''
[[Category:Chess Programmer|Sabatelli]]
[[Category:Researcher|Sabatelli]]
[[FILE:MatthiaSabatelli.jpg|border|right|thumb| Matthia Sabatelli <ref>[https://paintception.github.io/ Matthia Sabatelli]</ref> ]]
'''Matthia Sabatelli''',<br/>
an Italian computer scientist and Ph.D. candidate at [https://en.wikipedia.org/wiki/University_of_Li%C3%A8ge University of Liège],
researching on [https://en.wikipedia.org/wiki/Transfer_learning transfer learning] which bridges between [[Supervised Learning|supervised]] and [[Deep Learning|deep]] [[Reinforcement Learning|reinforcement learning]].
He holds a B.Sc. from [https://en.wikipedia.org/wiki/University_of_Trento University of Trento] in 2014, and a M.Sc. from [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen] in 2017 <ref>[https://www.linkedin.com/in/matthia-sabatelli-70370b93/ Matthia Sabatelli | LinkedIn]</ref>.
In his M.Sc thesis Matthia Sabatelli elaborates on [[Learning|learning]] to play chess with minimal [[Search|lookahead]], using [[Neural Networks#Deep|multilayer perceptrons]] versus [[Neural Networks#Convolutional|convolutional neural networks]] to approximate [[Stockfish|Stockfish’s]] [[Evaluation|evaluation]], also comparing two different [[Board Representation|board representations]] for the input layer
<ref>[[Matthia Sabatelli]] ('''2017'''). ''Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks''. Master's thesis, [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen], [https://www.ai.rug.nl/~mwiering/Thesis_Matthia_Sabatelli.pdf pdf]</ref>.
=Selected Publications=
<ref>[https://dblp.org/pid/160/6434.html dblp: Matthia Sabatelli]</ref>
==2017 ...==
* [[Matthia Sabatelli]] ('''2017'''). ''Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks''. Master's thesis, [https://en.wikipedia.org/wiki/University_of_Groningen University of Groningen], [https://www.ai.rug.nl/~mwiering/Thesis_Matthia_Sabatelli.pdf pdf] <ref>[https://github.com/paintception/DeepChess GitHub - paintception/DeepChess]</ref>
* [[Matthia Sabatelli]], [[Francesco Bidoia]], [[Valeriu Codreanu]], [[Marco Wiering]] ('''2018'''). ''Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead''. ICPRAM 2018, [https://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/ICPRAM_CHESS_DNN_2018.pdf pdf]
* [[Matthia Sabatelli]], [https://github.com/glouppe Gilles Louppe], [https://scholar.google.com/citations?user=tyFTsmIAAAAJ&hl=en Pierre Geurts], [[Marco Wiering]] ('''2018'''). ''Deep Quality-Value (DQV) Learning''. [https://arxiv.org/abs/1810.00368 arXiv:1810.00368]
* [[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 ...==
* [[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://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]
=External Links=
* [https://www.linkedin.com/in/matthia-sabatelli-70370b93/ Matthia Sabatelli | LinkedIn]
* [https://paintception.github.io/ Matthia Sabatelli]
* [https://scholar.google.com/citations?user=YO2Php8AAAAJ&hl=en Matthia Sabatelli - Google Scholar]
* [https://github.com/paintception paintception (Matthia Sabatelli) · GitHub]
=References=
<references />
'''[[People|Up one Level]]'''
[[Category:Chess Programmer|Sabatelli]]
[[Category:Researcher|Sabatelli]]
