Speaker: Karol Arndt
Robotics Seminar Series. Fifth Session – 22nd May 2020, 13:00-14:00, via zoom. Link to event: https://aalto.zoom.us/j/62124942899
In recent years, meta learning has seen increasing attention in the machine learning and robotics communities. In this presentation, I will provide an introduction and overview to meta-learning techniques: what problems they’re trying to solve, what basic algorithms can be used to solve these problems, and how the existing methods can be applied in the context of reinforcement learning.
- C. Finn et al., Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks, 2017, https://arxiv.org/abs/1703.03400
- P. Ortega et al., Meta-learning of Sequential Strategies, 2019, https://arxiv.org/abs/1905.03030
- E. Grant et al, Recasting Gradient-Based Meta-Learning as Hierarchical Bayes, 2018, https://arxiv.org/abs/1801.08930
- B. Stadie et al., Some Considerations on Learning to Explore via Meta-Reinforcement Learning, 2018, https://arxiv.org/abs/1803.011