Concrete Problems in AI Safety

21 June 2016

Papers citing "Concrete Problems in AI Safety"

26 / 476 papers shown

Title
DropoutDAgger: A Bayesian Approach to Safe Imitation Learning Kunal Menda Katherine Driggs-Campbell Mykel J. Kochenderfer 29 28 0 18 Sep 2017
Guidelines for Artificial Intelligence Containment James Babcock János Kramár Roman V. Yampolskiy 20 30 0 24 Jul 2017
Trial without Error: Towards Safe Reinforcement Learning via Human Intervention William Saunders Girish Sastry Andreas Stuhlmuller Owain Evans OffRL 24 229 0 17 Jul 2017
Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning Daniel S. Brown S. Niekum BDL OffRL 22 42 0 03 Jul 2017
An In-Depth Analysis of Visual Tracking with Siamese Neural Networks R. Pflugfelder 19 14 0 03 Jul 2017
Deep reinforcement learning from human preferences Paul Christiano Jan Leike Tom B. Brown Miljan Martic Shane Legg Dario Amodei 13 3,118 0 12 Jun 2017
Reinforcement Learning with a Corrupted Reward Channel Tom Everitt Victoria Krakovna Laurent Orseau Marcus Hutter Shane Legg 20 100 0 23 May 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 48 585 0 22 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 65 2,699 0 19 May 2017
Repeated Inverse Reinforcement Learning Kareem Amin Nan Jiang Satinder Singh 8 75 0 15 May 2017
Probabilistically Safe Policy Transfer David Held Zoe McCarthy Michael Zhang Fred Shentu Pieter Abbeel 24 19 0 15 May 2017
Maximum Resilience of Artificial Neural Networks Chih-Hong Cheng Georg Nührenberg Harald Ruess AAML 27 281 0 28 Apr 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems Hossein Hosseini Yize Chen Sreeram Kannan Baosen Zhang Radha Poovendran AAML 30 106 0 13 Mar 2017
Dropout Inference in Bayesian Neural Networks with Alpha-divergences Yingzhen Li Y. Gal UQCV BDL 49 196 0 08 Mar 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,503 0 25 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,683 0 05 Dec 2016
Generalizing Skills with Semi-Supervised Reinforcement Learning Chelsea Finn Tianhe Yu Justin Fu Pieter Abbeel Sergey Levine OffRL SSL 29 68 0 01 Dec 2016
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems Besmira Nushi Ece Kamar Eric Horvitz Donald Kossmann 42 77 0 24 Nov 2016
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 932 0 21 Oct 2016
Learning Optimized Risk Scores Berk Ustun Cynthia Rudin 17 82 0 01 Oct 2016
Towards Verified Artificial Intelligence S. Seshia Dorsa Sadigh S. Shankar Sastry 20 203 0 27 Jun 2016
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 720 0 12 May 2016
Fairness Constraints: Mechanisms for Fair Classification Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 114 49 0 19 Jul 2015
Toward Idealized Decision Theory N. Soares Benja Fallenstein 21 37 0 07 Jul 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,156 0 06 Jun 2015
Safe Exploration in Markov Decision Processes T. Moldovan Pieter Abbeel 78 308 0 22 May 2012