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ORCIDAlexander Novikov 0001
Person information
- affiliation: DeepMind
- affiliation: Russian Academy of Sciences, Marchuk Institute of Numerical Mathematics, Moscow, Russia
- affiliation: National Research University Higher School of Economics, Moscow, Russia
- affiliation (former): Skolkovo Institute of Science and Technology, Moscow, Russia
Other persons with the same name
- Alexander Novikov 0002
![[0000-0001-8529-173X]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-8529-173X")
— University of Technology Sydney, School of Mathematical and Physical Sciences, NSW, Australia (and 1 more) - Alexander Novikov 0003 — Moscow Aviation Institute (National Research University), Russia
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Journal Articles
- 2025
[j7]Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli:
Quantum circuit optimization with AlphaTensor. Nat. Mac. Intell. 7(3): 374-385 (2025)- 2024
- [j6]Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi:
Mathematical discoveries from program search with large language models. Nat. 625(7995): 468-475 (2024) - 2022
- [j5]Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli:
Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. 610(7930): 47-53 (2022) - [j4]Alexander Novikov, Maxim V. Rakhuba, Ivan V. Oseledets:
Automatic Differentiation for Riemannian Optimization on Low-Rank Matrix and Tensor-Train Manifolds. SIAM J. Sci. Comput. 44(2): 843- (2022) - [j3]Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas:
A Generalist Agent. Trans. Mach. Learn. Res. 2022 (2022) - 2020
- [j2]Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets:
Tensor Train Decomposition on TensorFlow (T3F). J. Mach. Learn. Res. 21: 30:1-30:7 (2020) - 2019
- [j1]Maxim V. Rakhuba, Alexander Novikov, Ivan V. Oseledets:
Low-rank Riemannian eigensolver for high-dimensional Hamiltonians. J. Comput. Phys. 396: 718-737 (2019)
Conference and Workshop Papers
- 2021
- [c10]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:
Benchmarks for Deep Off-Policy Evaluation. ICLR 2021 - 2020
- [c9]Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gómez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang:
Task-Relevant Adversarial Imitation Learning. CoRL 2020: 247-263 - [c8]Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas:
Critic Regularized Regression. NeurIPS 2020 - [c7]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas:
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS 2020 - [c6]Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang:
Scaling data-driven robotics with reward sketching and batch reinforcement learning. Robotics: Science and Systems 2020 - 2018
- [c5]Pavel Izmailov, Alexander Novikov, Dmitry Kropotov:
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. AISTATS 2018: 726-735 - [c4]Valentin Khrulkov, Alexander Novikov, Ivan V. Oseledets:
Expressive power of recurrent neural networks. ICLR (Poster) 2018 - 2017
- [c3]Alexander Novikov, Mikhail Trofimov, Ivan V. Oseledets:
Exponential Machines. ICLR (Workshop) 2017 - 2015
- [c2]Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov:
Tensorizing Neural Networks. NIPS 2015: 442-450 - 2014
- [c1]Alexander Novikov, Anton Rodomanov, Anton Osokin, Dmitry P. Vetrov:
Putting MRFs on a Tensor Train. ICML 2014: 811-819
Informal and Other Publications
- 2024
- [i19]Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli:
Quantum Circuit Optimization with AlphaTensor. CoRR abs/2402.14396 (2024) - [i18]Petar Velickovic, Alex Vitvitskyi, Larisa Markeeva, Borja Ibarz, Lars Buesing, Matej Balog, Alexander Novikov:
Amplifying human performance in combinatorial competitive programming. CoRR abs/2411.19744 (2024) - 2022
- [i17]Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas:
A Generalist Agent. CoRR abs/2205.06175 (2022) - 2021
- [i16]Alexander Novikov, Maxim V. Rakhuba, Ivan V. Oseledets:
Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds. CoRR abs/2103.14974 (2021) - [i15]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:
Benchmarks for Deep Off-Policy Evaluation. CoRR abs/2103.16596 (2021) - 2020
- [i14]Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas:
Acme: A Research Framework for Distributed Reinforcement Learning. CoRR abs/2006.00979 (2020) - [i13]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas:
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR abs/2006.13888 (2020) - [i12]Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas:
Critic Regularized Regression. CoRR abs/2006.15134 (2020) - [i11]Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas:
Hyperparameter Selection for Offline Reinforcement Learning. CoRR abs/2007.09055 (2020) - [i10]Konrad Zolna, Alexander Novikov, Ksenia Konyushkova, Çaglar Gülçehre, Ziyu Wang, Yusuf Aytar, Misha Denil, Nando de Freitas, Scott E. Reed:
Offline Learning from Demonstrations and Unlabeled Experience. CoRR abs/2011.13885 (2020) - [i9]Ksenia Konyushkova, Konrad Zolna, Yusuf Aytar, Alexander Novikov, Scott E. Reed, Serkan Cabi, Nando de Freitas:
Semi-supervised reward learning for offline reinforcement learning. CoRR abs/2012.06899 (2020) - 2019
- [i8]Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott E. Reed, Rae Jeong, Konrad Zolna, Yusuf Aytar, David Budden, Mel Vecerík, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang:
A Framework for Data-Driven Robotics. CoRR abs/1909.12200 (2019) - [i7]Konrad Zolna, Scott E. Reed, Alexander Novikov, Sergio Gomez Colmenarejo, David Budden, Serkan Cabi, Misha Denil, Nando de Freitas, Ziyu Wang:
Task-Relevant Adversarial Imitation Learning. CoRR abs/1910.01077 (2019) - 2018
- [i6]Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V. Oseledets:
Tensor Train decomposition on TensorFlow (T3F). CoRR abs/1801.01928 (2018) - 2017
- [i5]Pavel Izmailov, Alexander Novikov, Dmitry Kropotov:
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition. CoRR abs/1710.07324 (2017) - [i4]Valentin Khrulkov, Alexander Novikov, Ivan V. Oseledets:
Expressive power of recurrent neural networks. CoRR abs/1711.00811 (2017) - 2016
- [i3]Alexander Novikov, Mikhail Trofimov, Ivan V. Oseledets:
Tensor Train polynomial models via Riemannian optimization. CoRR abs/1605.03795 (2016) - [i2]Timur Garipov, Dmitry Podoprikhin, Alexander Novikov, Dmitry P. Vetrov:
Ultimate tensorization: compressing convolutional and FC layers alike. CoRR abs/1611.03214 (2016) - 2015
- [i1]Alexander Novikov, Dmitry Podoprikhin, Anton Osokin, Dmitry P. Vetrov:
Tensorizing Neural Networks. CoRR abs/1509.06569 (2015)
Coauthor Index
aka: Sergio Gómez Colmenarejo
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