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A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design.
Keyi Wu
Peng Chen
Omar Ghattas
Published in:
CoRR (2020)
Keyphrases
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computational framework
experimental design
high dimensional
stochastic dynamic programming
computational model
experimental designs
active learning
empirical studies
feature selection
sample size
nearest neighbor
machine learning
training set
high dimensional data
learning systems
class imbalance