Bayesian Generational Population-Based Training

19 July 2022

Xingchen Wan

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Papers citing "Bayesian Generational Population-Based Training"

29 / 29 papers shown

Title
Approximate Neural Architecture Search via Operation Distribution Learning Xingchen Wan Binxin Ru P. Esperança Fabio Maria Carlucci 72 7 0 08 Nov 2021
Replay-Guided Adversarial Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Jakob N. Foerster Edward Grefenstette Tim Rocktaschel 194 102 0 06 Oct 2021
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization Marius Lindauer Katharina Eggensperger Matthias Feurer André Biedenkapp Difan Deng C. Benjamins Tim Ruhopf René Sass Frank Hutter 124 345 0 20 Sep 2021
Open-Ended Learning Leads to Generally Capable Agents Open-Ended Learning Team Adam Stooke Anuj Mahajan Catarina Barros Charlie Deck ... Nicolas Porcel Roberta Raileanu Steph Hughes-Fitt Valentin Dalibard Wojciech M. Czarnecki 103 189 0 27 Jul 2021
From Motor Control to Team Play in Simulated Humanoid Football Siqi Liu Guy Lever Zhe Wang J. Merel S. M. Ali Eslami ... Tuomas Haarnoja Brendan D. Tracey K. Tuyls T. Graepel N. Heess 110 131 0 25 May 2021
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization Julia Guerrero-Viu Sven Hauns Sergio Izquierdo Guilherme Miotto Simon Schrodi André Biedenkapp T. Elsken Difan Deng Marius Lindauer Frank Hutter AI4CE 55 27 0 03 May 2021
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search Y. Fu Zhongzhi Yu Yongan Zhang Yingyan Lin 57 4 0 24 Dec 2020
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design Michael Dennis Natasha Jaques Eugene Vinitsky Alexandre M. Bayen Stuart J. Russell Andrew Critch Sergey Levine 81 236 0 03 Dec 2020
Deep Reinforcement Learning for Efficient Measurement of Quantum Devices Vu-Linh Nguyen S. B. Orbell D. Lennon H. Moon F. Vigneau ... D. Zumbuhl G. Briggs Michael A. Osborne D. Sejdinovic N. Ares 49 41 0 30 Sep 2020
Sample-Efficient Automated Deep Reinforcement Learning Jörg Franke Gregor Koehler André Biedenkapp Frank Hutter 78 41 0 03 Sep 2020
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search Vu-Linh Nguyen Tam Le M. Yamada Michael A. Osborne AI4TS 71 39 0 13 Jun 2020
Transient Non-Stationarity and Generalisation in Deep Reinforcement Learning Maximilian Igl Gregory Farquhar Jelena Luketina Wendelin Boehmer Shimon Whiteson 75 88 0 10 Jun 2020
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions Rui Wang Joel Lehman Aditya Rawal Jiale Zhi Yulun Li Jeff Clune Kenneth O. Stanley 82 129 0 19 Mar 2020
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits Jack Parker-Holder Vu Nguyen Stephen J. Roberts OffRL 122 86 0 06 Feb 2020
Leveraging Procedural Generation to Benchmark Reinforcement Learning K. Cobbe Christopher Hesse Jacob Hilton John Schulman 79 557 0 03 Dec 2019
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search Colin White Willie Neiswanger Yash Savani BDL 107 323 0 25 Oct 2019
Scalable Global Optimization via Local Bayesian Optimization Samyam Rajbhandari Michael Pearce Jacob R. Gardner Ryan D. Turner Matthias Poloczek 86 473 0 03 Oct 2019
Bayesian Optimization in AlphaGo Yutian Chen Aja Huang Ziyun Wang Ioannis Antonoglou Julian Schrittwieser David Silver Nando de Freitas BDL 68 114 0 17 Dec 2018
A Tutorial on Bayesian Optimization P. Frazier GP 111 1,788 0 08 Jul 2018
Human-level performance in first-person multiplayer games with population-based deep reinforcement learning Max Jaderberg Wojciech M. Czarnecki Iain Dunning Luke Marris Guy Lever ... Joel Z Leibo David Silver Demis Hassabis Koray Kavukcuoglu T. Graepel OffRL 110 727 0 03 Jul 2018
DARTS: Differentiable Architecture Search Hanxiao Liu Karen Simonyan Yiming Yang 199 4,361 0 24 Jun 2018
Neural Architecture Search with Bayesian Optimisation and Optimal Transport Kirthevasan Kandasamy Willie Neiswanger J. Schneider Barnabás Póczós Eric Xing 79 609 0 11 Feb 2018
Population Based Training of Neural Networks Max Jaderberg Valentin Dalibard Simon Osindero Wojciech M. Czarnecki Jeff Donahue ... Tim Green Iain Dunning Karen Simonyan Chrisantha Fernando Koray Kavukcuoglu 79 743 0 27 Nov 2017
Deep Reinforcement Learning that Matters Peter Henderson Riashat Islam Philip Bachman Joelle Pineau Doina Precup David Meger OffRL 118 1,961 0 19 Sep 2017
Time-Varying Gaussian Process Bandit Optimization Ilija Bogunovic Jonathan Scarlett Volkan Cevher 103 98 0 25 Jan 2016
Non-stochastic Best Arm Identification and Hyperparameter Optimization Kevin Jamieson Ameet Talwalkar 208 580 0 27 Feb 2015
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 127 12,261 0 19 Dec 2013
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning E. Brochu Vlad M. Cora Nando de Freitas GP 138 2,448 0 12 Dec 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 149 1,623 0 21 Dec 2009