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Remi Tachet des Combes
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He is broadly interested in improving deep / reinforcement learning models. This encompasses deep learning theory – from a learning dynamics and generalization standpoint, generalization in RL – essentially via representation learning, and safe RL.
Papers22 papers
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IJCAI 2020, pp.2847-2854, (2020)
NIPS 2020, (2020)
The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, 2019, (2019)
IEEE Transactions on Intelligent Transportation Systems, (2019)
arXiv: Learning, (2019)
Autonomous Agents and Multi-Agent Systems, pp.1269-1277, (2019)
AISTATS, pp.3514-3524, (2019)
international conference on machine learning, pp.3652-3661, (2019)
arXiv: Learning, (2018)
ICLR, (2018)
arXiv: Computation and Language, (2018)
Scientific Reports, no. 1 (2017): 42868
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Journal of Mathematical Finance, no. 03 (2017): 571-596
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(2014)
BigData Congress, pp.136-143, (2014)
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