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Jakub Sygnowski

2 accepted papers

2023

Human-Timescale Adaptation in an Open-Ended Task Space

ICML 2023oral

Foundation models have shown impressive adaptation and scalability in supervised and self-supervised learning problems, but so far these successes have not fully translated to reinforcement learning (RL). In this work, we demonstrate that training an RL agent at scale leads to a general in-context l…

Cited by 111SourcePDFScholar
2019

Meta-Learning with Latent Embedding Optimization

ICLR 2019poster

Gradient-based meta-learning techniques are both widely applicable and proficient at solving challenging few-shot learning and fast adaptation problems. However, they have practical difficulties when operating on high-dimensional parameter spaces in extreme low-data regimes. We show that it is possi…