A Heuristic Sampling Method for Maintaining the Probability Distribution

[1]  Nir Friedman,et al.  Bayesian Network Classifiers , 1997, Machine Learning.

[2]  Jiao-Yun Yang,et al.  Sampling to Maintain Approximate Probability Distribution Under Chi-Square Test , 2019, NCTCS.

[3]  Jimmy J. Lin,et al.  Sampling Strategies and Active Learning for Volume Estimation , 2016, SIGIR.

[4]  Cristina Conati,et al.  On-Line Student Modeling for Coached Problem Solving Using Bayesian Networks , 1997 .

[5]  Luca Martino,et al.  Improved Adaptive Rejection Metropolis Sampling Algorithms , 2012 .

[6]  Costas Papadimitriou,et al.  Bayesian Annealed Sequential Importance Sampling: An Unbiased Version of Transitional Markov Chain Monte Carlo , 2018 .

[7]  K. Pearson.  On the Criterion that a Given System of Deviations from the Probable in the Case of a Correlated System of Variables is Such that it Can be Reasonably Supposed to have Arisen from Random Sampling , 1900 .

[8]  Gil Alterovitz,et al.  Subtype dependent biomarker identification and tumor classification from gene expression profiles , 2018, Knowl. Based Syst..

[9]  Sharon L. Lohr,et al.  Sampling: Design and Analysis , 1999 .

[10]  C. Goodhart,et al.  High frequency data in financial markets: Issues and applications , 1997 .

[11]  Caspar G. Chorus,et al.  Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis , 2018, Journal of Choice Modelling.

[12]  Gregory F. Cooper,et al.  The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks , 1989, AIME.