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Geoffrey Gordon

2 accepted papers

2019

On Learning Invariant Representations for Domain Adaptation

ICML 2019oral

Due to the ability of deep neural nets to learn rich representations, recent advances in unsupervised domain adaptation have focused on learning domain-invariant features that achieve a small error on the source domain. The hope is that the learnt representation, together with the hypothesis learnt…

Cited by 769SourcePDFScholar
2018

Recurrent Predictive State Policy Networks

ICML 2018oral

We introduce Recurrent Predictive State Policy(RPSP) networks, a recurrent architecture that brings insights from predictive state representations to reinforcement learning in partially ob-servable environments. Predictive state policy networks consist of a recursive filter, which keeps track of a b…