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Assistant HES, PhD student CS UNIGE lionel.blonde@hesge.ch |
Bio
Lionel Blondé has been working as PhD student in the Data Mining and Machine Learning team since early 2015. Before, he completed his master degree in Applied Mathematics and Computer Science in the French engineering school ENSEEIHT, from 2011 to 2014.
Research
Lionel is interested in training simulated agents to complete locomotion tasks, developing Reinforcement Learning and Imitation Learning algorithms. He is particularly interested in overcoming the deterring sample inefficiency of previous methods tackling similar problems.
Publications
2019 |
Sample-Efficient Imitation Learning via Generative Adversarial Nets Inproceedings The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, pp. 3138–3148, 2019. |
2018 |
Sample-Efficient Imitation Learning via Generative Adversarial Nets Conference abs/1809.02064 , 2018. |