基本信息
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职业迁徙
个人简介
The ultimate goal of my research is contributing to human-level artificial general intelligence (AGI). One of the most central aspects of AGI is its ability to generalize to novel tasks, and in order to understand this ability I have explored meta-learning, a higher-level learning framework that allows a model to learn to generalize over a distribution of tasks rather than generalize within a single task. During my Ph.D. study I have tried to extend the scope of meta-learning towards more realistic, practical, and large-scale scenarios. For future research agenda, I aim to study meta-reinforcement learning (meta-RL) and meta-continual learning (meta-CL) to better understand the way human being interact with the environments. Based on those understandings I aim to develop a human-level RL agent that can generalize to out-of-distribution tasks and continually learn from them. This is closely related to the concept of system 2 deep learning (DL), which, from the meta-learning point of view, can be realized by incorporating higher-level cognitive concepts into the meta-knowledge structure.
研究兴趣
论文共 23 篇作者统计合作学者相似作者
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Jean-Pierre René Falet,Hae Beom Lee,Nikolay Malkin,Chen Sun,Dragos Secrieru,Dinghuai Zhang,Guillaume Lajoie,Yoshua Bengio
ICLR (2024)
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CoRR (2024)
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INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139 (2021)
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17
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作者统计
#Papers: 23
#Citation: 488
H-Index: 10
G-Index: 13
Sociability: 4
Diversity: 2
Activity: 33
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