81 citations
- Google (United States)US4 papers
- Centre Universitaire de MilaDZ2 papers
- Columbia UniversityUS2 papers
- Google DeepMind (United Kingdom)GB2 papers
- Kao Corporation (Japan)JP2 papers
- Université de MontréalCA2 papers
- Berlin Institute for the Foundations of Learning and DataDE1 paper
- Bernstein Center for Computational Neuroscience FreiburgDE1 paper
- Center for Pain and the BrainUS1 paper
- Center for Visual Communication (United States)US1 paper
- Douglas Mental Health University InstituteCA1 paper
- Duke UniversityUS1 paper
Showing 2020 · cs.LGShow all
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cs.LG2020★ 81 cited
Revisiting Fundamentals of Experience Replay
William Fedus, Prajit Ramachandran, Rishabh Agarwal +4
Experience replay is central to off-policy algorithms in deep reinforcement learning (RL), but there remain significant gaps in our understanding. We therefore present a systematic…
cs.LG2020★ 1 cited
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo +1
Conventional sequential learning methods such as Recurrent Neural Networks (RNNs) focus on interactions between consecutive inputs, i.e. first-order Markovian dependency. However,…