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Jack Parker-Holder
Jack Parker-Holder
Research Scientist at DeepMind
Bestätigte E-Mail-Adresse bei google.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Effective Diversity in Population Based Reinforcement Learning
J Parker-Holder*, A Pacchiano*, K Choromanski, S Roberts
NeurIPS 2020 (Spotlight), 2020
622020
From Complexity to Simplicity: Adaptive ES-Active Subspaces for Blackbox Optimization
KM Choromanski*, A Pacchiano*, J Parker-Holder*, Y Tang*, ...
Advances in Neural Information Processing Systems, 10299-10309, 2019
302019
Ready Policy One: World Building Through Active Learning
P Ball*, J Parker-Holder*, A Pacchiano, K Choromanski, S Roberts
ICML 2020, 2020
282020
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
J Parker-Holder, V Nguyen, S Roberts
NeurIPS 2020, 2020
282020
Provably Robust Blackbox Optimization for Reinforcement Learning
K Choromanski*, A Pacchiano*, J Parker-Holder*, Y Tang, D Jain, Y Yang, ...
Conference on Robot Learning, 683-696, 2019
26*2019
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
M Samvelyan, R Kirk, V Kurin, J Parker-Holder, M Jiang, E Hambro, ...
NeurIPS 2021 (Datasets and Benchmarks), 2021
22*2021
Towards Tractable Optimism in Model-Based Reinforcement Learning
A Pacchiano*, P Ball*, J Parker-Holder*, K Choromanski, S Roberts
UAI 2021, 2020
19*2020
Learning to Score Behaviors for Guided Policy Optimization
A Pacchiano*, J Parker-Holder*, Y Tang*, K Choromanski, ...
International Conference on Machine Learning, 7445-7454, 2020
172020
Replay-Guided Adversarial Environment Design
M Jiang*, M Dennis*, J Parker-Holder, J Foerster, E Grefenstette, ...
NeurIPS 2021, 2021
132021
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
J Parker-Holder*, L Metz, C Resnick, H Hu, A Lerer, A Letcher, ...
Advances in Neural Information Processing Systems 33, 2020
132020
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
J Parker-Holder*, R Rajan*, X Song*, A Biedenkapp, Y Miao, T Eimer, ...
JAIR, 2022
122022
Tactical Optimism and Pessimism for Deep Reinforcement Learning
T Moskovitz, J Parker-Holder, A Pacchiano, M Arbel, MI Jordan
NeurIPS 2021, 2021
12*2021
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment
PJ Ball*, C Lu*, J Parker-Holder, S Roberts
ICML 2021, 2021
82021
ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution
X Song, KM Choromanski, J Parker-Holder, Y Tang, D Peng, D Jain, ...
6*2021
Evolving Curricula with Regret-Based Environment Design
J Parker-Holder*, M Jiang*, M Dennis, M Samvelyan, J Foerster, ...
ICML 2022, 2022
52022
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL
J Parker-Holder, V Nguyen, S Desai, S Roberts
NeurIPS 2021, 2021
52021
Graph Kernel Attention Transformers
K Choromanski, H Lin, H Chen, J Parker-Holder
arXiv preprint arXiv:2107.07999, 2021
42021
Stochastic Flows and Geometric Optimization on the Orthogonal Group
K Choromanski, D Cheikhi, J Davis, V Likhosherstov, A Nazaret, ...
ICML 2020, 2020
42020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes
K Choromanski*, A Pacchiano*, J Parker-Holder*, Y Tang*
International Conference on Artificial Intelligence and Statistics, 1363-1374, 2020
3*2020
Insights From the NeurIPS 2021 NetHack Challenge
E Hambro, S Mohanty, D Babaev, M Byeon, D Chakraborty, ...
arXiv preprint arXiv:2203.11889, 2022
22022
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