Fetching the paper…
Reading the bibliography…
We study the problem of safe learning and exploration in sequential control problems.
The effect of ground on a helicopter rotor in forward flight
IC Cheeseman and WE Bennett · 1955
Earlier work this paper cites.
Applied nonlinear control , volume 199
Jean-Jacques E Slotine, Weiping Li, et al · 1991
Earlier work this paper cites.
Essentials of robust control , volume 104
Kemin Zhou and John Comstock Doyle · 1998
Earlier work this paper cites.
Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira · 2000
Earlier work this paper cites.
Using confidence bounds for exploitation-exploration trade-offs
Peter Auer · 2002
Earlier work this paper cites.
Nonlinear systems
Hassan Khalil and Jessy Grizzle · 2002
Earlier work this paper cites.
Game theory, maximum entropy, minimum discrepancy and robust bayesian decision theory
Peter D Grünwald, A Philip Dawid, et al · 2004
Earlier work this paper cites.
Multi-task gaussian process prediction
Edwin V Bonilla, Kian M Chai, and Christopher Williams · 2008
Earlier work this paper cites.
Gaussian process optimization in the bandit setting: No regret and experimental design
Niranjan Srinivas, Andreas Krause, Sham M Kakade, and Matthias Seeger · 2010
Earlier work this paper cites.
Regret analysis of stochastic and nonstochastic multi-armed bandit problems
Sébastien Bubeck, Nicolo Cesa-Bianchi, et al · 2012
Earlier work this paper cites.
Safe exploration of state and action spaces in reinforcement learning
Javier Garcia and Fernando Fernández · 2012
Earlier work this paper cites.
Safe exploration in markov decision processes
Teodor Mihai Moldovan and Pieter Abbeel · 2012
Earlier work this paper cites.
Learning object class detectors from weakly annotated video
Alessandro Prest, Christian Leistner, Javier Civera, Cordelia Schmid, and Vittorio Ferrari · 2012
Earlier work this paper cites.
Dropout training as adaptive regularization
Stefan Wager, Sida Wang, and Percy S Liang · 2013
Earlier work this paper cites.
Reachability-based safe learning with gaussian processes
Anayo K Akametalu, Jaime F Fisac, Jeremy H Gillula, Shahab Kaynama, Melanie N Zeilinger, and Claire J Tomlin · 2014
Cited alongside, same era.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
Cited alongside, same era.
Robust classification under sample selection bias
Anqi Liu and Brian Ziebart · 2014
Cited alongside, same era.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
Cited alongside, same era.
Shift-pessimistic active learning using robust bias-aware prediction
Anqi Liu, Lev Reyzin, and Brian D Ziebart · 2015
Cited alongside, same era.
On the brittleness of bayesian inference
Safe model-based reinforcement learning with stability guarantees
Felix Berkenkamp, Matteo Turchetta, Angela Schoellig, and Andreas Krause · 2017
Later among the works it cites.
Robust covariate shift prediction with general losses and feature views
Anqi Liu and Brian D Ziebart · 2017
Later among the works it cites.
Label-free supervision of neural networks with physics and domain knowledge
Russell Stewart and Stefano Ermon · 2017
Later among the works it cites.
Safe reinforcement learning via shielding
Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, and Ufuk Topcu · 2018
Later among the works it cites.
A general safety framework for learning-based control in uncertain robotic systems
Jaime F Fisac, Anayo K Akametalu, Melanie N Zeilinger, Shahab Kaynama, Jeremy Gillula, and Claire J Tomlin · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Houman Owhadi, Clint Scovel, and Tim Sullivan · 2015
Cited alongside, same era.
Safe exploration for optimization with gaussian processes
Yanan Sui, Alkis Gotovos, Joel Burdick, and Andreas Krause · 2015
Cited alongside, same era.
Safe controller optimization for quadrotors with gaussian processes
Felix Berkenkamp, Angela P Schoellig, and Andreas Krause · 2016
Cited alongside, same era.
Robust covariate shift regression
Xiangli Chen, Mathew Monfort, Anqi Liu, and Brian D Ziebart · 2016
Cited alongside, same era.
Smooth imitation learning for online sequence prediction
Hoang M. Le, Andrew Kang, Yisong Yue, and Peter Carr · 2016
Cited alongside, same era.
Robust constrained learning-based nmpc enabling reliable mobile robot path tracking
Chris J Ostafew, Angela P Schoellig, and Timothy D Barfoot · 2016
Cited alongside, same era.
Safe exploration in finite markov decision processes with gaussian processes
Matteo Turchetta, Felix Berkenkamp, and Andreas Krause · 2016
Cited alongside, same era.
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
Later among the works it cites.
Stagewise safe bayesian optimization with gaussian processes
Yanan Sui, Vincent Zhuang, Joel W Burdick, and Yisong Yue · 2018
Later among the works it cites.
Safe exploration and optimization of constrained mdps using gaussian processes
Akifumi Wachi, Yanan Sui, Yisong Yue, and Masahiro Ono · 2018
Later among the works it cites.
Measuring and regularizing networks in function space
Ari S Benjamin, David Rolnick, and Konrad Kording · 2019
Closest in time.
Adaptive and safe bayesian optimization in high dimensions via one-dimensional subspaces
Johannes Kirschner, Mojmír Mutnỳ, Nicole Hiller, Rasmus Ischebeck, and Andreas Krause · 2019
Closest in time.
Trajectory optimization for chance-constrained nonlinear stochastic systems
Yashwanth Kumar Nakka and Soon-Jo Chung · 2019
Closest in time.
Neural lander: Stable drone landing control using learned dynamics
Guanya Shi, Xichen Shi, Michael O’Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, and Soon-Jo Chung · 2019
Closest in time.
Episodic learning with control lyapunov functions for uncertain robotic systems
Andrew J Taylor, Victor D Dorobantu, Hoang M Le, Yisong Yue, and Aaron D Ames · 2019
Closest in time.