Preparing for Black Swans: The Antifragility Imperative for Machine Learning

18 May 2024

Papers citing "Preparing for Black Swans: The Antifragility Imperative for Machine Learning"

35 / 35 papers shown

Title
Quality-Diversity through AI Feedback Herbie Bradley Andrew M. Dai H. Teufel Jenny Zhang Koen Oostermeijer Marco Bellagente Jeff Clune Kenneth O. Stanley Grégory Schott Joel Lehman 17 26 0 19 Oct 2023
Safe Exploration in Reinforcement Learning: A Generalized Formulation and Algorithms Akifumi Wachi Wataru Hashimoto Xun Shen Kazumune Hashimoto 53 10 0 05 Oct 2023
Retrieving Multimodal Information for Augmented Generation: A Survey Ruochen Zhao Hailin Chen Weishi Wang Fangkai Jiao Do Xuan Long ... Bosheng Ding Xiaobao Guo Minzhi Li Xingxuan Li Shafiq Joty 72 85 0 20 Mar 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 49 20 0 31 Jan 2023
Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models Nikolaos Dimitriadis P. Frossard Franccois Fleuret 55 25 0 18 Oct 2022
A Generalist Agent Scott E. Reed Konrad Zolna Emilio Parisotto Sergio Gomez Colmenarejo Alexander Novikov ... Yutian Chen R. Hadsell Oriol Vinyals Mahyar Bordbar Nando de Freitas LM&Ro LLMAG AI4CE 167 801 0 12 May 2022
Factored Adaptation for Non-Stationary Reinforcement Learning Fan Feng Erdun Gao Kun Zhang Sara Magliacane CML OffRL 100 32 0 30 Mar 2022
Tight Concentrations and Confidence Sequences from the Regret of Universal Portfolio Francesco Orabona Kwang-Sung Jun 82 41 0 27 Oct 2021
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 221 282 0 28 Sep 2021
Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning Lukas Brunke Melissa Greeff Adam W. Hall Zhaocong Yuan Siqi Zhou Jacopo Panerati Angela P. Schoellig OffRL 48 610 0 13 Aug 2021
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning Erdun Gao Fan Feng Chaochao Lu Sara Magliacane Kun Zhang 76 66 0 06 Jul 2021
RL for Latent MDPs: Regret Guarantees and a Lower Bound Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor 44 78 0 09 Feb 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 146 1,418 0 14 Dec 2020
Learning to be Safe: Deep RL with a Safety Critic K. Srinivasan Benjamin Eysenbach Sehoon Ha Jie Tan Chelsea Finn OffRL 58 143 0 27 Oct 2020
Conservative Safety Critics for Exploration Homanga Bharadhwaj Aviral Kumar Nicholas Rhinehart Sergey Levine Florian Shkurti Animesh Garg OffRL 74 139 0 27 Oct 2020
Learning the Pareto Front with Hypernetworks Aviv Navon Aviv Shamsian Gal Chechik Ethan Fetaya 99 142 0 08 Oct 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo D. Song Jacob Steinhardt Justin Gilmer OOD 257 1,715 0 29 Jun 2020
Optimizing for the Future in Non-Stationary MDPs Yash Chandak Georgios Theocharous Shiv Shankar Martha White Sridhar Mahadevan Philip S. Thomas OffRL 35 65 0 17 May 2020
Meta-Learning in Neural Networks: A Survey Timothy M. Hospedales Antreas Antoniou P. Micaelli Amos Storkey OOD 300 1,950 0 11 Apr 2020
Gradient Surgery for Multi-Task Learning Tianhe Yu Saurabh Kumar Abhishek Gupta Sergey Levine Karol Hausman Chelsea Finn 114 1,190 0 19 Jan 2020
Single Episode Policy Transfer in Reinforcement Learning Jiachen Yang Brenden K. Petersen H. Zha Daniel Faissol OOD OffRL 108 33 0 17 Oct 2019
Introduction to Online Convex Optimization Elad Hazan OffRL 90 1,922 0 07 Sep 2019
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation Runzhe Yang Xingyuan Sun Karthik Narasimhan 56 252 0 21 Aug 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 109 3,399 0 28 Mar 2019
Provably efficient RL with Rich Observations via Latent State Decoding S. Du A. Krishnamurthy Nan Jiang Alekh Agarwal Miroslav Dudík John Langford OffRL 45 230 0 25 Jan 2019
Evolved Policy Gradients Rein Houthooft Richard Y. Chen Phillip Isola Bradly C. Stadie Filip Wolski Jonathan Ho Pieter Abbeel 79 226 0 13 Feb 2018
Online Learning: A Comprehensive Survey Guosheng Lin Doyen Sahoo Jing Lu P. Zhao OffRL 53 638 0 08 Feb 2018
Learning to reinforcement learn Jane X. Wang Z. Kurth-Nelson Dhruva Tirumala Hubert Soyer Joel Z Leibo Rémi Munos Charles Blundell D. Kumaran M. Botvinick OffRL 73 974 0 17 Nov 2016
RL $^2$ : Fast Reinforcement Learning via Slow Reinforcement Learning Yan Duan John Schulman Xi Chen Peter L. Bartlett Ilya Sutskever Pieter Abbeel OffRL 67 1,011 0 09 Nov 2016
Matrix Completion has No Spurious Local Minimum Rong Ge Jason D. Lee Tengyu Ma 53 597 0 24 May 2016
On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities Alexander Rakhlin Karthik Sridharan 43 48 0 13 Oct 2015
Non-stationary Stochastic Optimization Omar Besbes Y. Gur A. Zeevi 111 430 0 20 Jul 2013
Online Learning with Predictable Sequences Alexander Rakhlin Karthik Sridharan 112 355 0 18 Aug 2012
Predictive State Representations: A New Theory for Modeling Dynamical Systems Satinder Singh Michael R. James Matthew R. Rudary AI4TS AI4CE 63 288 0 11 Jul 2012
On the Computational Complexity of Stochastic Controller Optimization in POMDPs N. Vlassis Michael L. Littman David Barber 68 84 0 15 Jul 2011