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Benchmarks for Deep Off-Policy Evaluation


Mar 30, 2021
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine

* ICLR 2021 paper. Policies and evaluation code are available at https://github.com/google-research/deep_ope 

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Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds


Mar 27, 2021
Alexander Novikov, Maxim Rakhuba, Ivan Oseledets


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Semi-supervised reward learning for offline reinforcement learning


Dec 12, 2020
Ksenia Konyushkova, Konrad Zolna, Yusuf Aytar, Alexander Novikov, Scott Reed, Serkan Cabi, Nando de Freitas

* Accepted to Offline Reinforcement Learning Workshop at Neural Information Processing Systems (2020) 

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Offline Learning from Demonstrations and Unlabeled Experience


Nov 27, 2020
Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Caglar Gulcehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott Reed

* Accepted to Offline Reinforcement Learning Workshop at Neural Information Processing Systems (2020) 

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Hyperparameter Selection for Offline Reinforcement Learning


Jul 17, 2020
Tom Le Paine, Cosmin Paduraru, Andrea Michi, Caglar Gulcehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas


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RL Unplugged: Benchmarks for Offline Reinforcement Learning


Jul 02, 2020
Caglar Gulcehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gomez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas

* 21 pages including supplementary material, the github link for the datasets: https://github.com/deepmind/deepmind-research/rl_unplugged 

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Critic Regularized Regression


Jun 26, 2020
Ziyu Wang, Alexander Novikov, Konrad Żołna, Jost Tobias Springenberg, Scott Reed, Bobak Shahriari, Noah Siegel, Josh Merel, Caglar Gulcehre, Nicolas Heess, Nando de Freitas

* 23 pages 

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Task-Relevant Adversarial Imitation Learning


Oct 02, 2019
Konrad Zolna, Scott Reed, Alexander Novikov, Sergio Gomez Colmenarej, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang


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A Framework for Data-Driven Robotics


Sep 26, 2019
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott Reed, Rae Jeong, Konrad Żołna, Yusuf Aytar, David Budden, Mel Vecerik, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang


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Expressive power of recurrent neural networks


Feb 07, 2018
Valentin Khrulkov, Alexander Novikov, Ivan Oseledets

* Accepted as a conference paper at ICLR 2018 

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Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition


Jan 17, 2018
Pavel Izmailov, Alexander Novikov, Dmitry Kropotov


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Exponential Machines


Dec 08, 2017
Alexander Novikov, Mikhail Trofimov, Ivan Oseledets

* ICLR-2017 workshop track paper 

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Ultimate tensorization: compressing convolutional and FC layers alike


Nov 10, 2016
Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry Vetrov

* NIPS 2016 workshop: Learning with Tensors: Why Now and How? 

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Tensorizing Neural Networks


Dec 20, 2015
Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry Vetrov


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