Concrete Problems in AI Safety

21 June 2016

Papers citing "Concrete Problems in AI Safety"

50 / 475 papers shown

Title
A Distributional View on Multi-Objective Policy Optimization A. Abdolmaleki Sandy H. Huang Leonard Hasenclever Michael Neunert H. F. Song Martina Zambelli M. Martins N. Heess R. Hadsell Martin Riedmiller 21 74 0 15 May 2020
Reinforcement Learning with Augmented Data Michael Laskin Kimin Lee Adam Stooke Lerrel Pinto Pieter Abbeel A. Srinivas OffRL 20 647 0 30 Apr 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 41 371 0 30 Apr 2020
First return, then explore Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune 47 351 0 27 Apr 2020
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization Dongsheng Ding Xiaohan Wei Zhuoran Yang Zhaoran Wang M. Jovanović 20 159 0 01 Mar 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 2020
Learning in Markov Decision Processes under Constraints Rahul Singh Abhishek Gupta Ness B. Shroff 44 27 0 27 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences Daniel S. Brown Russell Coleman R. Srinivasan S. Niekum BDL 30 101 0 21 Feb 2020
Distributionally Robust Bayesian Optimization Johannes Kirschner Ilija Bogunovic Stefanie Jegelka Andreas Krause 30 77 0 20 Feb 2020
AI safety: state of the field through quantitative lens Mislav Juric A. Sandic Mario Brčič 25 24 0 12 Feb 2020
Reaching, Grasping and Re-grasping: Learning Multimode Grasping Skills Wenbin Hu Chuanyu Yang Kai Yuan Zhibin Li 25 5 0 11 Feb 2020
Importance-Driven Deep Learning System Testing Simos Gerasimou Hasan Ferit Eniser A. Sen Alper Çakan AAML VLM 30 98 0 09 Feb 2020
Minimax Defense against Gradient-based Adversarial Attacks Blerta Lindqvist R. Izmailov AAML 19 0 0 04 Feb 2020
Adversarial Machine Learning -- Industry Perspectives Ramnath Kumar Magnus Nyström J. Lambert Andrew Marshall Mario Goertzel Andi Comissoneru Matt Swann Sharon Xia AAML SILM 29 232 0 04 Feb 2020
Constrained Upper Confidence Reinforcement Learning Liyuan Zheng Lillian J. Ratliff 28 67 0 26 Jan 2020
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks Oliver Willers Sebastian Sudholt Shervin Raafatnia Stephanie Abrecht 28 80 0 22 Jan 2020
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation Letian Chen Rohan R. Paleja Muyleng Ghuy Matthew C. Gombolay 14 38 0 02 Jan 2020
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning Andreas Sedlmeier Thomas Gabor Thomy Phan Lenz Belzner Claudia Linnhoff-Popien 21 25 0 31 Dec 2019
Dirichlet uncertainty wrappers for actionable algorithm accuracy accountability and auditability José Mena O. Pujol Jordi Vitrià 21 8 0 29 Dec 2019
A Survey of Deep Learning Applications to Autonomous Vehicle Control Sampo Kuutti Richard Bowden Yaochu Jin P. Barber Saber Fallah 36 506 0 23 Dec 2019
SafeLife 1.0: Exploring Side Effects in Complex Environments Carroll L. Wainwright P. Eckersley 27 12 0 03 Dec 2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation Alireza Mehrtash W. Wells C. Tempany Purang Abolmaesumi Tina Kapur OOD FedML UQCV 24 265 0 29 Nov 2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models Tong Che Xiaofeng Liu Site Li Yubin Ge Ruixiang Zhang Caiming Xiong Yoshua Bengio 38 52 0 18 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 18 104 0 13 Nov 2019
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning J. Liu John Paisley M. Kioumourtzoglou B. Coull UQCV UD PER 30 83 0 11 Nov 2019
Fully Bayesian Recurrent Neural Networks for Safe Reinforcement Learning Matthew Benatan Edward O. Pyzer-Knapp BDL 24 6 0 08 Nov 2019
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey Olakunle Ibitoye Rana Abou-Khamis Mohamed el Shehaby Ashraf Matrawy M. O. Shafiq AAML 37 68 0 06 Nov 2019
Convergent Policy Optimization for Safe Reinforcement Learning Ming Yu Zhuoran Yang Mladen Kolar Zhaoran Wang 16 91 0 26 Oct 2019
Addressing Failure Prediction by Learning Model Confidence Charles Corbière Nicolas Thome Avner Bar-Hen Matthieu Cord P. Pérez 33 283 0 01 Oct 2019
Emergent Tool Use From Multi-Agent Autocurricula Bowen Baker I. Kanitscheider Todor Markov Yi Wu Glenn Powell Bob McGrew Igor Mordatch LRM 37 646 0 17 Sep 2019
Density estimation in representation space to predict model uncertainty Tiago Ramalho M. Corbalan UQCV BDL 16 38 0 20 Aug 2019
Implications of Quantum Computing for Artificial Intelligence alignment research Jaime Sevilla Pablo Moreno 16 1 0 19 Aug 2019
Deep reinforcement learning in World-Earth system models to discover sustainable management strategies Felix M. Strnad W. Barfuss J. Donges J. Heitzig 30 25 0 15 Aug 2019
Deep Learning for Detecting Building Defects Using Convolutional Neural Networks H. Perez J. Tah Amir H. Mosavi 15 194 0 06 Aug 2019
The Role of Cooperation in Responsible AI Development Amanda Askell Miles Brundage Gillian Hadfield 33 60 0 10 Jul 2019
Learning the Arrow of Time Nasim Rahaman Steffen Wolf Anirudh Goyal Roman Remme Yoshua Bengio 14 5 0 02 Jul 2019
Interpretable Image Recognition with Hierarchical Prototypes Peter Hase Chaofan Chen Oscar Li Cynthia Rudin VLM 17 111 0 25 Jun 2019
Non-Parametric Calibration for Classification Jonathan Wenger Hedvig Kjellström Rudolph Triebel UQCV 45 79 0 12 Jun 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 50 716 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 29 1,658 0 06 Jun 2019
A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives Alexander Fabisch Christoph Petzoldt M. Otto Frank Kirchner AI4CE 15 13 0 05 Jun 2019
Risks from Learned Optimization in Advanced Machine Learning Systems Evan Hubinger Chris van Merwijk Vladimir Mikulik Joar Skalse Scott Garrabrant 45 146 0 05 Jun 2019
Asymptotically Unambitious Artificial General Intelligence Michael K. Cohen Badri N. Vellambi Marcus Hutter ELM AI4CE 12 17 0 29 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network Oscar Chang Yuling Yao David Williams-King Hod Lipson BDL UQCV 32 8 0 23 May 2019
Detecting Adversarial Examples and Other Misclassifications in Neural Networks by Introspection Jonathan Aigrain Marcin Detyniecki AAML 27 30 0 22 May 2019
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 27 231 0 30 Apr 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 11 36 0 16 Apr 2019
Tutorial: Safe and Reliable Machine Learning Suchi Saria Adarsh Subbaswamy FaML 30 82 0 15 Apr 2019
Neural Network Model Extraction Attacks in Edge Devices by Hearing Architectural Hints Xing Hu Ling Liang Lei Deng Shuangchen Li Xinfeng Xie Yu Ji Yufei Ding Chang Liu T. Sherwood Yuan Xie AAML MLAU 23 36 0 10 Mar 2019