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LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery
We introduce LOTUS, a continual imitation learning algorithm that empowers a physical robot to continuously and efficiently learn to solve new manipulation tasks throughout its lifespan.
Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing
Unsupervised domain adaptation which aims to adapt models trained on a labeled source domain to a completely unlabeled target domain has attracted much attention in recent years.
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Unsupervised Domain Adaptation
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