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2020 – today
- 2024
- [c37]Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel:
Multi-Agent Diagnostics for Robustness via Illuminated Diversity. AAMAS 2024: 1630-1644 - [c36]Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. ICML 2024 - [c35]Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. ICML 2024 - [c34]Sherry Yang, Jacob C. Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, André Barreto, Pieter Abbeel, Dale Schuurmans:
Position: Video as the New Language for Real-World Decision Making. ICML 2024 - [i46]Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel:
Multi-Agent Diagnostics for Robustness via Illuminated Diversity. CoRR abs/2401.13460 (2024) - [i45]Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. CoRR abs/2402.15391 (2024) - [i44]Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H. Markosyan, Manish Bhatt, Yuning Mao, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Tim Rocktäschel, Roberta Raileanu:
Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. CoRR abs/2402.16822 (2024) - [i43]Sherry Yang, Jacob C. Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, André Barreto, Pieter Abbeel, Dale Schuurmans:
Video as the New Language for Real-World Decision Making. CoRR abs/2402.17139 (2024) - [i42]Davide Paglieri, Saurabh Dash, Tim Rocktäschel, Jack Parker-Holder:
Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs. CoRR abs/2405.20835 (2024) - [i41]Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Open-Endedness is Essential for Artificial Superhuman Intelligence. CoRR abs/2406.04268 (2024) - 2023
- [j2]Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh:
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. Trans. Mach. Learn. Res. 2023 (2023) - [c33]Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos:
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs 2023: 184-204 - [c32]Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel:
Stabilizing Unsupervised Environment Design with a Learned Adversary. CoLLAs 2023: 270-291 - [c31]Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel:
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. ICLR 2023 - [c30]Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. ICML 2023: 1887-1935 - [c29]Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster:
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. NeurIPS 2023 - [c28]Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder:
Synthetic Experience Replay. NeurIPS 2023 - [i40]Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. CoRR abs/2301.07608 (2023) - [i39]Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Roberta Raileanu, Tim Rocktäschel:
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. CoRR abs/2303.03376 (2023) - [i38]Cong Lu, Philip J. Ball, Jack Parker-Holder:
Synthetic Experience Replay. CoRR abs/2303.06614 (2023) - [i37]Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel:
Stabilizing Unsupervised Environment Design with a Learned Adversary. CoRR abs/2308.10797 (2023) - [i36]Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster:
Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. CoRR abs/2310.02782 (2023) - [i35]Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang:
Vision-Language Models as a Source of Rewards. CoRR abs/2312.09187 (2023) - 2022
- [j1]Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp
, Yingjie Miao, Theresa Eimer
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. J. Artif. Intell. Res. 74: 517-568 (2022) - [c27]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI 2022: 7143-7151 - [c26]Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano:
Towards an Understanding of Default Policies in Multitask Policy Optimization. AISTATS 2022: 10661-10686 - [c25]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. AAMAS 2022: 842-852 - [c24]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. AAMAS 2022: 1771-1773 - [c23]Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne:
Bayesian Generational Population-Based Training. AutoML 2022: 14/1-27 - [c22]Michael T. Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette, Tim Rocktäschel:
Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning. CoLLAs 2022: 856-874 - [c21]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR 2022 - [c20]Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten:
From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML 2022: 3962-3983 - [c19]Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel:
Evolving Curricula with Regret-Based Environment Design. ICML 2022: 17473-17498 - [c18]Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster:
Grounding Aleatoric Uncertainty for Unsupervised Environment Design. NeurIPS 2022 - [c17]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. NeurIPS 2022 - [i34]Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. CoRR abs/2201.03916 (2022) - [i33]Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel:
Evolving Curricula with Regret-Based Environment Design. CoRR abs/2203.01302 (2022) - [i32]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. CoRR abs/2203.08015 (2022) - [i31]Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin
Insights From the NeurIPS 2021 NetHack Challenge. CoRR abs/2203.11889 (2022) - [i30]Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh:
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. CoRR abs/2206.04779 (2022) - [i29]Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster:
Grounding Aleatoric Uncertainty in Unsupervised Environment Design. CoRR abs/2207.05219 (2022) - [i28]Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne:
Bayesian Generational Population-Based Training. CoRR abs/2207.09405 (2022) - [i27]Michael T. Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette, Tim Rocktäschel:
Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning. CoRR abs/2207.11584 (2022) - [i26]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. CoRR abs/2210.12719 (2022) - [i25]Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts:
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. CoRR abs/2211.15944 (2022) - 2021
- [c16]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML 2021: 619-629 - [c15]Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski:
Insights From the NeurIPS 2021 NetHack Challenge. NeurIPS (Competition and Demos) 2021: 41-52 - [c14]Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel:
Replay-Guided Adversarial Environment Design. NeurIPS 2021: 1884-1897 - [c13]Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel, Michael I. Jordan:
Tactical Optimism and Pessimism for Deep Reinforcement Learning. NeurIPS 2021: 12849-12863 - [c12]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. NeurIPS 2021: 15513-15528 - [c11]Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel:
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. NeurIPS Datasets and Benchmarks 2021 - [c10]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
Towards tractable optimism in model-based reinforcement learning. UAI 2021: 1413-1423 - [i24]Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang:
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. CoRR abs/2101.07415 (2021) - [i23]Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel:
Deep Reinforcement Learning with Dynamic Optimism. CoRR abs/2102.03765 (2021) - [i22]Krzysztof Choromanski, Deepali Jain, Jack Parker-Holder, Xingyou Song, Valerii Likhosherstov, Anirban Santara, Aldo Pacchiano, Yunhao Tang, Adrian Weller:
Unlocking Pixels for Reinforcement Learning via Implicit Attention. CoRR abs/2102.04353 (2021) - [i21]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR abs/2104.05632 (2021) - [i20]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR abs/2106.02940 (2021) - [i19]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. CoRR abs/2106.15883 (2021) - [i18]Krzysztof Choromanski, Han Lin, Haoxian Chen, Jack Parker-Holder:
Graph Kernel Attention Transformers. CoRR abs/2107.07999 (2021) - [i17]Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel:
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. CoRR abs/2109.13202 (2021) - [i16]Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel:
Replay-Guided Adversarial Environment Design. CoRR abs/2110.02439 (2021) - [i15]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR abs/2110.04135 (2021) - [i14]Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano:
Towards an Understanding of Default Policies in Multitask Policy Optimization. CoRR abs/2111.02994 (2021) - [i13]Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster:
Lyapunov Exponents for Diversity in Differentiable Games. CoRR abs/2112.14570 (2021) - 2020
- [c9]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang:
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes. AISTATS 2020: 1363-1374 - [c8]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts:
Ready Policy One: World Building Through Active Learning. ICML 2020: 591-601 - [c7]Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao
Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML 2020: 1918-1928 - [c6]Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael I. Jordan:
Learning to Score Behaviors for Guided Policy Optimization. ICML 2020: 7445-7454 - [c5]Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob N. Foerster:
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. NeurIPS 2020 - [c4]Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts:
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. NeurIPS 2020 - [c3]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts:
Effective Diversity in Population Based Reinforcement Learning. NeurIPS 2020 - [i12]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Effective Diversity in Population-Based Reinforcement Learning. CoRR abs/2002.00632 (2020) - [i11]Jack Parker-Holder, Vu Nguyen, Stephen Roberts:
One-Shot Bayes Opt with Probabilistic Population Based Training. CoRR abs/2002.02518 (2020) - [i10]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Ready Policy One: World Building Through Active Learning. CoRR abs/2002.02693 (2020) - [i9]Krzysztof Choromanski, David Cheikhi, Jared Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamás Sarlós, Adrian Weller, Vikas Sindhwani:
Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR abs/2003.13563 (2020) - [i8]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
On Optimism in Model-Based Reinforcement Learning. CoRR abs/2006.11911 (2020) - [i7]Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alex Peysakhovich, Aldo Pacchiano, Jakob N. Foerster:
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. CoRR abs/2011.06505 (2020)
2010 – 2019
- 2019
- [c2]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Deepali Jain, Yuxiang Yang, Atil Iscen, Jasmine Hsu, Vikas Sindhwani:
Provably Robust Blackbox Optimization for Reinforcement Learning. CoRL 2019: 683-696 - [c1]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Vikas Sindhwani:
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization. NeurIPS 2019: 10299-10309 - [i6]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Jasmine Hsu, Atil Iscen, Deepali Jain, Vikas Sindhwani:
When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. CoRR abs/1903.02993 (2019) - [i5]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang:
Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces. CoRR abs/1903.04268 (2019) - [i4]Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang:
Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes. CoRR abs/1905.12667 (2019) - [i3]Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Anna Choromanska, Krzysztof Choromanski, Michael I. Jordan:
Wasserstein Reinforcement Learning. CoRR abs/1906.04349 (2019) - [i2]Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang:
Reinforcement Learning with Chromatic Networks. CoRR abs/1907.06511 (2019) - 2018
- [i1]Jack Parker-Holder, Sam Gass:
Compressing Deep Neural Networks: A New Hashing Pipeline Using Kac's Random Walk Matrices. CoRR abs/1801.02764 (2018)
Coauthor Index
Krzysztof Choromanski
aka: Krzysztof Marcin Choromanski
aka: Krzysztof Marcin Choromanski
Michael Dennis 0001
aka: Michael D. Dennis
aka: Michael D. Dennis
Jakob N. Foerster
aka: Jakob Nicolaus Foerster
aka: Jakob Nicolaus Foerster
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