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Published in 2021 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2020.1753522
Abstract: Abstract–Q-learning is a regression-based approach that is widely used to formalize the development of an optimal dynamic treatment strategy. Finite dimensional working models are typically used to estimate certain nuisance parameters, and misspecification of these…
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Keywords:
robust learning;
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Published in 2022 at "Big data"
DOI: 10.1089/big.2021.0064
Abstract: Artificial neural networks (ANNs) have been frequently used in forecasting problems in recent years. One of the most popular types of ANNs in these days is Pi-Sigma artificial neural networks (PS-ANNs). PS-ANNs have a high…
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Keywords:
neural networks;
algorithm based;
sigma artificial;
robust learning ... See more keywords
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Published in 2019 at "IEEE Transactions on Robotics"
DOI: 10.1109/tro.2019.2891173
Abstract: In this paper, we focus on the problem of learning from demonstration (LfD) where demonstrations with different proficiencies are provided without labeling. To this end, we model multiple policies with different qualities as correlated Gaussian…
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Keywords:
mixed qualities;
qualities using;
gaussian processes;
learning demonstrations ... See more keywords
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Published in 2019 at "PLoS ONE"
DOI: 10.1371/journal.pone.0218183
Abstract: The blooms of Noctiluca in the Gulf of Oman and the Arabian Sea have been intensifying in recent years, posing now a threat to regional fisheries and the long-term health of an ecosystem supporting a…
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Keywords:
robust learning;
noctiluca blooms;
oceanography;
local scale ... See more keywords