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Tom Le Paine
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2020 – today
- 2023
- [i18]Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci, Tom Le Paine, Yutian Chen, Misha Denil:
π2vec: Policy Representations with Successor Features. CoRR abs/2306.09800 (2023) - [i17]Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Çaglar Gülçehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Richard Powell, Konrad Zolna, Julian Schrittwieser, David H. Choi, Petko Georgiev, Daniel Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo, Aäron van den Oord, Wojciech Marian Czarnecki, Nando de Freitas, Oriol Vinyals:
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. CoRR abs/2308.03526 (2023) - [i16]Çaglar Gülçehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, Nando de Freitas:
Reinforced Self-Training (ReST) for Language Modeling. CoRR abs/2308.08998 (2023) - 2022
- [j2]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. J. Mach. Learn. Res. 23: 302:1-302:40 (2022) - 2021
- [c7]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 - [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) - [i14]Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi:
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. CoRR abs/2104.13877 (2021) - [i13]Yutian Chen, Liyuan Xu, Çaglar Gülçehre, Tom Le Paine, Arthur Gretton, Nando de Freitas, Arnaud Doucet:
On Instrumental Variable Regression for Deep Offline Policy Evaluation. CoRR abs/2105.10148 (2021) - 2020
- [c6]Çaglar Gülçehre, Tom Le Paine, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team:
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. ICLR 2020 - [i12]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) - [i11]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) - [i10]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)
2010 – 2019
- 2019
- [j1]Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds
, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch
, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver:
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - [i9]Tom Le Paine, Çaglar Gülçehre, Bobak Shahriari, Misha Denil, Matt Hoffman, Hubert Soyer, Richard Tanburn, Steven Kapturowski, Neil C. Rabinowitz, Duncan Williams, Gabriel Barth-Maron, Ziyu Wang, Nando de Freitas, Worlds Team:
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. CoRR abs/1909.01387 (2019) - [i8]Albert Gu, Çaglar Gülçehre, Tom Le Paine, Matthew W. Hoffman, Razvan Pascanu:
Improving the Gating Mechanism of Recurrent Neural Networks. CoRR abs/1910.09890 (2019) - 2018
- [c5]Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas:
Playing hard exploration games by watching YouTube. NeurIPS 2018: 2935-2945 - [i7]Yusuf Aytar, Tobias Pfaff, David Budden, Tom Le Paine, Ziyu Wang, Nando de Freitas:
Playing hard exploration games by watching YouTube. CoRR abs/1805.11592 (2018) - [i6]Tom Le Paine, Sergio Gomez Colmenarejo, Ziyu Wang, Scott E. Reed, Yusuf Aytar, Tobias Pfaff, Matthew W. Hoffman, Gabriel Barth-Maron, Serkan Cabi, David Budden, Nando de Freitas:
One-Shot High-Fidelity Imitation: Training Large-Scale Deep Nets with RL. CoRR abs/1810.05017 (2018) - 2017
- [c4]Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark A. Hasegawa-Johnson, Roy H. Campbell, Thomas S. Huang:
Fast Generation for Convolutional Autoregressive Models. ICLR (Workshop) 2017 - [i5]Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark A. Hasegawa-Johnson, Roy H. Campbell, Thomas S. Huang:
Fast Generation for Convolutional Autoregressive Models. CoRR abs/1704.06001 (2017) - 2016
- [c3]Pooya Khorrami, Tom Le Paine, Kevin Brady, Charlie K. Dagli, Thomas S. Huang:
How deep neural networks can improve emotion recognition on video data. ICIP 2016: 619-623 - [i4]Pooya Khorrami, Tom Le Paine, Kevin Brady, Charlie K. Dagli, Thomas S. Huang:
How Deep Neural Networks Can Improve Emotion Recognition on Video Data. CoRR abs/1602.07377 (2016) - [i3]Wei Han, Pooya Khorrami, Tom Le Paine, Prajit Ramachandran, Mohammad Babaeizadeh, Honghui Shi, Jianan Li, Shuicheng Yan, Thomas S. Huang:
Seq-NMS for Video Object Detection. CoRR abs/1602.08465 (2016) - [i2]Tom Le Paine, Pooya Khorrami, Shiyu Chang, Yang Zhang, Prajit Ramachandran, Mark A. Hasegawa-Johnson, Thomas S. Huang:
Fast Wavenet Generation Algorithm. CoRR abs/1611.09482 (2016) - 2015
- [c2]Pooya Khorrami, Tom Le Paine, Thomas S. Huang:
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition? ICCV Workshops 2015: 19-27 - [c1]Tom Le Paine, Pooya Khorrami, Wei Han, Thomas S. Huang:
An Analysis of Unsupervised Pre-training in Light of Recent Advances. ICLR (Workshop) 2015 - [i1]Pooya Khorrami, Tom Le Paine, Thomas S. Huang:
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition? CoRR abs/1510.02969 (2015)
Coauthor Index
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last updated on 2024-08-10 00:28 CEST by the dblp team
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