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Many real-world situations allow for the acquisition of additional relevant information when making an assessment with limited or uncertain data.
On the likelihood that one unknown probability exceeds another in view of the evidence of two samples
William R Thompson · 1933
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Local computations with probabilities on graphical structures and their application to expert systems
Steffen L Lauritzen and David J Spiegelhalter · 1988
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Information-based objective functions for active data selection
David JC MacKay · 1992
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Bayesian network induction via local neighborhoods
Dimitris Margaritis and Sebastian Thrun · 2000
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Bayesian network repository, 2001
G. Elidan · 2001
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Learning equivalence classes of bayesian-network structures
David Maxwell Chickering · 2002
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Pruning improves heuristic search for cost-sensitive learning
Valentina Bayer Zubek and Thomas G Dietterich · 2002
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Estimating mutual information
Alexander Kraskov, Harald Stögbauer, and Peter Grassberger · 2004
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Test-cost sensitive naive bayes classification
Xiaoyong Chai, Lin Deng, Qiang Yang, and Charles X Ling · 2004
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Decision trees with minimal costs
Charles X Ling, Qiang Yang, Jianning Wang, and Shichao Zhang · 2004
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Feature value acquisition in testing: a sequential batch test algorithm
Victor S Sheng and Charles X Ling · 2006
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Using markov blankets for causal structure learning
Jean-Philippe Pellet and André Elisseeff · 2008
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Active learning literature survey
Burr Settles · 2009
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Bayesian active learning for classification and preference learning
Neil Houlsby, Ferenc Huszár, Zoubin Ghahramani, and Máté Lengyel · 2011
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Sequential feature selection for classification
Thomas Rückstieß, Christian Osendorfer, and Patrick van der Smagt · 2011
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Uncertainty in deep learning
Yarin Gal · 2016
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A tutorial on thompson sampling
Daniel Russo, Benjamin Van Roy, Abbas Kazerouni, Ian Osband, and Zheng Wen · 2017
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The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
A. Bagnall, J. Lines, A. Bostrom, J. Large, and E. Keogh · 2017
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Joint active feature acquisition and classification with variable-size set encoding
Hajin Shim, Sung Ju Hwang, and Eunho Yang · 2018
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Eddi: Efficient dynamic discovery of high-value information with partial vae
Chao Ma, Sebastian Tschiatschek, Konstantina Palla, José Miguel Hernández-Lobato, Sebastian Nowozin, and Cheng Zhang · 2018
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Uci machine learning repository, 2013
M. Lichman · 2013
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A survey on feature selection methods
Girish Chandrashekar and Ferat Sahin · 2014
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Fast margin-based cost-sensitive classification
Feng Nan, Joseph Wang, Kirill Trapeznikov, and Venkatesh Saligrama · 2014
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Who learns better bayesian network structures: Constraint-based, score-based or hybrid algorithms?
Marco Scutari, Catharina Elisabeth Graafland, and José Manuel Gutiérrez · 2018
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Flow models for arbitrary conditional likelihoods
Yang Li, Shoaib Akbar, and Junier B Oliva · 2019
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Verified uncertainty calibration
Ananya Kumar, Percy S Liang, and Tengyu Ma · 2019
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A survey on bayesian network structure learning from data
Mauro Scanagatta, Antonio Salmerón, and Fabio Stella · 2019
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