Jack Parker-Holder

92 papers A* 26A 6Misc 1Journal 53Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. ICLR Davide Paglieri, Bartlomiej Cupial, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Lukasz Kucinski, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel
2025	J	`jnl`	Imagined Autocurricula. CoRR Ahmet Hamdi Güzel, Matthew Thomas Jackson, Jarek Liesen, Tim Rocktäschel, Jakob Nicolaus Foerster, Ilija Bogunovic, Jack Parker-Holder
2025	J	`jnl`	Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents. CoRR Davide Paglieri, Bartlomiej Cupial, Jonathan Cook, Ulyana Piterbarg, Jens Tuyls, Edward Grefenstette, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel
2025	J	`jnl`	Synthetic Data is Sufficient for Zero-Shot Visual Generalization from Offline Data. CoRR Ahmet Hamdi Güzel, Ilija Bogunovic, Jack Parker-Holder
2025	J	`jnl`	Synthetic Data is Sufficient for Zero-Shot Visual Generalization from Offline Data. Trans. Mach. Learn. Res. Ahmet Hamdi Güzel, Ilija Bogunovic, Jack Parker-Holder
2024	J	`jnl`	BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. CoRR Davide Paglieri, Bartlomiej Cupial, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Lukasz Kucinski, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel
2024	A*	`conf`	Genie: Generative Interactive Environments. ICML 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
2024	J	`jnl`	Genie: Generative Interactive Environments. CoRR 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
2024	A	`conf`	Multi-Agent Diagnostics for Robustness via Illuminated Diversity. AAMAS Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel
2024	J	`jnl`	Multi-Agent Diagnostics for Robustness via Illuminated Diversity. CoRR Mikayel Samvelyan, Davide Paglieri, Minqi Jiang, Jack Parker-Holder, Tim Rocktäschel
2024	J	`jnl`	Open-Endedness is Essential for Artificial Superhuman Intelligence. CoRR Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel
2024	J	`jnl`	Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs. CoRR Davide Paglieri, Saurabh Dash, Tim Rocktäschel, Jack Parker-Holder
2024	A*	`conf`	Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. ICML Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel
2024	A*	`conf`	Position: Video as the New Language for Real-World Decision Making. ICML Sherry Yang, Jacob C. Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, André Barreto, Pieter Abbeel, Dale Schuurmans
2024	A*	`conf`	Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. NeurIPS 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
2024	J	`jnl`	Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts. CoRR 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
2024	J	`jnl`	Video as the New Language for Real-World Decision Making. CoRR Sherry Yang, Jacob C. Walker, Jack Parker-Holder, Yilun Du, Jake Bruce, André Barreto, Pieter Abbeel, Dale Schuurmans
2023	J	`jnl`	Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. Trans. Mach. Learn. Res. Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh
2023	A*	`conf`	Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. NeurIPS Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob N. Foerster
2023	J	`jnl`	Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design. CoRR Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster
2023	A*	`conf`	Human-Timescale Adaptation in an Open-Ended Task Space. ICML 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
2023	J	`jnl`	Human-Timescale Adaptation in an Open-Ended Task Space. CoRR 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
2023	A*	`conf`	MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. ICLR Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster, Roberta Raileanu, Tim Rocktäschel
2023	J	`jnl`	MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. CoRR Mikayel Samvelyan, Akbir Khan, Michael Dennis, Minqi Jiang, Jack Parker-Holder, Jakob N. Foerster, Roberta Raileanu, Tim Rocktäschel
2023	—	`conf`	Stabilizing Unsupervised Environment Design with a Learned Adversary. CoLLAs Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel
2023	J	`jnl`	Stabilizing Unsupervised Environment Design with a Learned Adversary. CoRR Ishita Mediratta, Minqi Jiang, Jack Parker-Holder, Michael Dennis, Eugene Vinitsky, Tim Rocktäschel
2023	A*	`conf`	Synthetic Experience Replay. NeurIPS Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder
2023	J	`jnl`	Synthetic Experience Replay. CoRR Cong Lu, Philip J. Ball, Jack Parker-Holder
2023	—	`conf`	The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos
2023	J	`jnl`	Vision-Language Models as a Source of Rewards. CoRR 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
2022	J	`jnl`	Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. CoRR Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
2022	J	`jnl`	Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. J. Artif. Intell. Res. Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
2022	—	`conf`	Bayesian Generational Population-Based Training. AutoML Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne
2022	J	`jnl`	Bayesian Generational Population-Based Training. CoRR Xingchen Wan, Cong Lu, Jack Parker-Holder, Philip J. Ball, Vu Nguyen, Binxin Ru, Michael A. Osborne
2022	J	`jnl`	Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. CoRR Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A. Osborne, Yee Whye Teh
2022	A*	`conf`	Evolving Curricula with Regret-Based Environment Design. ICML Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
2022	J	`jnl`	Evolving Curricula with Regret-Based Environment Design. CoRR Jack Parker-Holder, Minqi Jiang, Michael Dennis, Mikayel Samvelyan, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
2022	A*	`conf`	From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. ICML Krzysztof Choromanski, Han Lin, Haoxian Chen, Tianyi Zhang, Arijit Sehanobish, Valerii Likhosherstov, Jack Parker-Holder, Tamás Sarlós, Adrian Weller, Thomas Weingarten
2022	A*	`conf`	Grounding Aleatoric Uncertainty for Unsupervised Environment Design. NeurIPS Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
2022	J	`jnl`	Grounding Aleatoric Uncertainty in Unsupervised Environment Design. CoRR Minqi Jiang, Michael Dennis, Jack Parker-Holder, Andrei Lupu, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel, Jakob N. Foerster
2022	—	`conf`	Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning. CoLLAs Michael T. Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette, Tim Rocktäschel
2022	J	`jnl`	Hierarchical Kickstarting for Skill Transfer in Reinforcement Learning. CoRR Michael T. Matthews, Mikayel Samvelyan, Jack Parker-Holder, Edward Grefenstette, Tim Rocktäschel
2022	J	`jnl`	Insights From the NeurIPS 2021 NetHack Challenge. CoRR 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
2022	A*	`conf`	Learning General World Models in a Handful of Reward-Free Deployments. NeurIPS Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette
2022	J	`jnl`	Learning General World Models in a Handful of Reward-Free Deployments. CoRR Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette
2022	A	`conf`	Lyapunov Exponents for Diversity in Differentiable Games. AAMAS Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster
2022	A	`conf`	On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. AAMAS Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts
2022	J	`jnl`	On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. CoRR Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts
2022	A*	`conf`	Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
2022	A*	`conf`	Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2022	J	`jnl`	The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. CoRR Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts
2022	A	`conf`	Towards an Understanding of Default Policies in Multitask Policy Optimization. AISTATS Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
2021	A*	`conf`	Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
2021	J	`jnl`	Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts
2021	J	`jnl`	Deep Reinforcement Learning with Dynamic Optimism. CoRR Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel
2021	J	`jnl`	ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning. CoRR Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Daiyi Peng, Deepali Jain, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Yuxiang Yang
2021	J	`jnl`	Graph Kernel Attention Transformers. CoRR Krzysztof Choromanski, Han Lin, Haoxian Chen, Jack Parker-Holder
2021	—	`conf`	Insights From the NeurIPS 2021 NetHack Challenge. NeurIPS (Competition and Demos) 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
2021	J	`jnl`	Lyapunov Exponents for Diversity in Differentiable Games. CoRR Jonathan Lorraine, Paul Vicol, Jack Parker-Holder, Tal Kachman, Luke Metz, Jakob N. Foerster
2021	—	`conf`	MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. NeurIPS Datasets and Benchmarks Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel
2021	J	`jnl`	MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research. CoRR Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, Tim Rocktäschel
2021	A*	`conf`	Replay-Guided Adversarial Environment Design. NeurIPS Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
2021	J	`jnl`	Replay-Guided Adversarial Environment Design. CoRR Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob N. Foerster, Edward Grefenstette, Tim Rocktäschel
2021	J	`jnl`	Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts
2021	J	`jnl`	Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2021	A*	`conf`	Tactical Optimism and Pessimism for Deep Reinforcement Learning. NeurIPS Ted Moskovitz, Jack Parker-Holder, Aldo Pacchiano, Michael Arbel, Michael I. Jordan
2021	J	`jnl`	Towards an Understanding of Default Policies in Multitask Policy Optimization. CoRR Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
2021	A	`conf`	Towards tractable optimism in model-based reinforcement learning. UAI Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts
2021	A*	`conf`	Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. NeurIPS Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts
2021	J	`jnl`	Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. CoRR Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts
2021	J	`jnl`	Unlocking Pixels for Reinforcement Learning via Implicit Attention. CoRR Krzysztof Choromanski, Deepali Jain, Jack Parker-Holder, Xingyou Song, Valerii Likhosherstov, Anirban Santara, Aldo Pacchiano, Yunhao Tang, Adrian Weller
2020	A*	`conf`	Effective Diversity in Population Based Reinforcement Learning. NeurIPS Jack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts
2020	J	`jnl`	Effective Diversity in Population-Based Reinforcement Learning. CoRR Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
2020	A*	`conf`	Learning to Score Behaviors for Guided Policy Optimization. ICML Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael I. Jordan
2020	J	`jnl`	On Optimism in Model-Based Reinforcement Learning. CoRR Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts
2020	J	`jnl`	One-Shot Bayes Opt with Probabilistic Population Based Training. CoRR Jack Parker-Holder, Vu Nguyen, Stephen Roberts
2020	A	`conf`	Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes. AISTATS Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang
2020	A*	`conf`	Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. NeurIPS Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts
2020	A*	`conf`	Ready Policy One: World Building Through Active Learning. ICML Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts
2020	J	`jnl`	Ready Policy One: World Building Through Active Learning. CoRR Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
2020	A*	`conf`	Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. NeurIPS Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob N. Foerster
2020	J	`jnl`	Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian. CoRR Jack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alex Peysakhovich, Aldo Pacchiano, Jakob N. Foerster
2020	A*	`conf`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. ICML 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
2020	J	`jnl`	Stochastic Flows and Geometric Optimization on the Orthogonal Group. CoRR 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
2019	J	`jnl`	Adaptive Sample-Efficient Blackbox Optimization via ES-active Subspaces. CoRR Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang
2019	A*	`conf`	From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization. NeurIPS Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Vikas Sindhwani
2019	Misc	`conf`	Provably Robust Blackbox Optimization for Reinforcement Learning. CoRL Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Deepali Jain, Yuxiang Yang, Atil Iscen, Jasmine Hsu, Vikas Sindhwani
2019	J	`jnl`	Reinforcement Learning with Chromatic Networks. CoRR Xingyou Song, Krzysztof Choromanski, Jack Parker-Holder, Yunhao Tang, Wenbo Gao, Aldo Pacchiano, Tamás Sarlós, Deepali Jain, Yuxiang Yang
2019	J	`jnl`	Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes. CoRR Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang
2019	J	`jnl`	Wasserstein Reinforcement Learning. CoRR Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Anna Choromanska, Krzysztof Choromanski, Michael I. Jordan
2019	J	`jnl`	When random search is not enough: Sample-Efficient and Noise-Robust Blackbox Optimization of RL Policies. CoRR Krzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Jasmine Hsu, Atil Iscen, Deepali Jain, Vikas Sindhwani
2018	J	`jnl`	Compressing Deep Neural Networks: A New Hashing Pipeline Using Kac's Random Walk Matrices. CoRR Jack Parker-Holder, Sam Gass