Victoria (Viktoriya) Krakovna
Victoria (Viktoriya) Krakovna
DeepMind
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AI safety gridworlds
J Leike, M Martic, V Krakovna, PA Ortega, T Everitt, A Lefrancq, L Orseau, ...
arXiv preprint arXiv:1711.09883, 2017
1252017
Reinforcement Learning with a Corrupted Reward Channel
T Everitt, V Krakovna, L Orseau, M Hutter, S Legg
IJCAI AI & Autonomy, 2017
432017
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models
V Krakovna, F Doshi-Velez
ICML Workshop on Human Interpretability (WHI 2016), arXiv preprint arXiv …, 2016
372016
Measuring and avoiding side effects using relative reachability
V Krakovna, L Orseau, M Martic, S Legg
arXiv preprint arXiv:1806.01186, 2018
122018
Specification gaming examples in AI
V Krakovna
tinyurl.com/specification-gaming, 2018
102018
Penalizing side effects using stepwise relative reachability
V Krakovna, L Orseau, R Kumar, M Martic, S Legg
arXiv preprint arXiv:1806.01186, 2018
72018
A generalized-zero-preserving method for compact encoding of concept lattices
M Skala, V Krakovna, J Kramár, G Penn
Proceedings of the 48th annual meeting of the Association for Computational …, 2010
52010
Modeling AGI safety frameworks with causal influence diagrams
T Everitt, R Kumar, V Krakovna, S Legg
arXiv preprint arXiv:1906.08663, 2019
42019
Interpretable selection and visualization of features and interactions using bayesian forests
V Krakovna, J Du, JS Liu
arXiv preprint arXiv:1506.02371, 2015
4*2015
A Minimalistic Approach to Sum-Product Network Learning for Real Applications
V Krakovna, M Looks
ICLR 2016 workshop, arXiv preprint arXiv:1602.04259, 2016
32016
Building interpretable models: From Bayesian networks to neural networks
V Krakovna
12016
Avoiding Side Effects By Considering Future Tasks
V Krakovna, L Orseau, M Martic, S Legg
NeurIPS Workshop on Safety and Robustness in Decision Making (https://drive …, 2019
2019
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Artiklar 1–12