基本信息
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职业迁徙
个人简介
Although my research has been primarily focused on Machine Learning and Mathematical Statistics, it turns out I am alo deeply enthousiastic about all areas in Mathematics and Computer Science, including things like Manifolds, Algebraic Topology, Differential Equations, Number theory, Category Theory, Topology, Information theory, Signal Processing, Lambda calculus, Algorithmic and Graph theory. I do have a strong bias towards the study of dynamical systems, because it somehow enables (and often requires) to combine a great number of areas from different parts of Mathematics and Computer Science. This may be also the reason why Reinforcement Learning is still not granted as much attention as it deserves, as being at the crossing of so many areas.
研究兴趣
论文共 111 篇作者统计合作学者相似作者
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arxiv(2023)
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International Conference on Algorithmic Learning Theory (2023): 74-124
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HAL (Le Centre pour la Communication Scientifique Directe) (2023)
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Romain Gautron,Emilio J. Padrón, Pierre‐Marie Preux, Julien Bigot,Odalric-Ambrym Maillard,Gerrit Hoogenboom, Julien Teigny
HAL (Le Centre pour la Communication Scientifique Directe) (2023)
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Asian Conference on Machine Learningpp.1167-1182, (2023)
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Timothée Mathieu,Riccardo Della Vecchia,Alena Shilova, Matheus Medeiros Centa, Hector Kohler,Odalric-Ambrym Maillard,Philippe Preux
CoRR (2023)
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Timothée Mathieu,Riccardo Della Vecchia,Alena Shilova, Marcelo C. Medeiros, Hector Kohler,Odalric-Ambrym Maillard, Pierre‐Marie Preux
arXiv (Cornell University) (2023)
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CoRR (2023)
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