References in zbMATH (referenced in 43 articles , 1 standard article )

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  1. Bedoui, Adel; Lazar, Nicole A.: Bayesian empirical likelihood for ridge and Lasso regressions (2020)
  2. Gabrielli, Andrea: A neural network boosted double overdispersed Poisson claims reserving model (2020)
  3. Sayan Putatunda, Dayananda Ubrangala, Kiran Rama, Ravi Kondapalli: DriveML: An R Package for Driverless Machine Learning (2020) arXiv
  4. Vencálek, Ondřej; Demni, Houyem; Messaoud, Amor; Porzio, Giovanni C.: On the optimality of the max-depth and max-rank classifiers for spherical data. (2020)
  5. Ahonen, Ilmari; Nevalainen, Jaakko; Larocque, Denis: Prediction with a flexible finite mixture-of-regressions (2019)
  6. Baltazar-Larios, F.; Esparza, Luz Judith R.: Bayesian estimation for the Markov-modulated diffusion risk model (2019)
  7. Bhadra, Anindya; Datta, Jyotishka; Polson, Nicholas G.; Willard, Brandon: Lasso meets horseshoe: a survey (2019)
  8. Chen, Li-Pang: Book review of: Mehryar Mohri et al., Foundations of machine learning. 2nd ed. (2019)
  9. Chen, Li-Pang; Yi, Grace Y.; Zhang, Qihuang; He, Wenqing: Multiclass analysis and prediction with network structured covariates (2019)
  10. Chen, Ying; Niu, Linlin; Chen, Ray-Bing; He, Qiang: Sparse-group independent component analysis with application to yield curves prediction (2019)
  11. Cossette, Hélène; Gadoury, Simon-Pierre; Marceau, Etienne; Robert, Christian Y.: Composite likelihood estimation method for hierarchical Archimedean copulas defined with multivariate compound distributions (2019)
  12. Huck, Nicolas: Large data sets and machine learning: applications to statistical arbitrage (2019)
  13. John, Boby; Kadadevaramath, Rajeshwar S.: Optimization of software development life cycle process to minimize the delivered defect density (2019)
  14. Lan, Guanghui; Yang, Yu: Accelerated stochastic algorithms for nonconvex finite-sum and multiblock optimization (2019)
  15. Liu, Lei; Shih, Ya-Chen Tina; Strawderman, Robert L.; Zhang, Daowen; Johnson, Bankole A.; Chai, Haitao: Statistical analysis of zero-inflated nonnegative continuous data: a review (2019)
  16. Sayan Putatunda, Kiran Rama, Dayananda Ubrangala, Ravi Kondapalli: SmartEDA: An R Package for Automated Exploratory Data Analysis (2019) arXiv
  17. Schmidt, Anatoly B.: Managing portfolio diversity within the mean variance theory (2019)
  18. Alves, Paulo Ricardo L.; Duarte, L. G. S.; da Mota, Luis Antonio Campinho Pereira: Detecting chaos and predicting in Dow Jones Index (2018)
  19. Bogaert, Matthias; Ballings, Michel; Van den Poel, Dirk: Evaluating the importance of different communication types in romantic tie prediction on social media (2018)
  20. de Caigny, Arno; Coussement, Kristof; de Bock, Koen W.: A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)

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