References in zbMATH (referenced in 1288 articles , 2 standard articles )

Showing results 41 to 60 of 1288.
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  1. Miasnikof, Pierre; Pitsoulis, Leonidas; Bonner, Anthony J.; Lawryshyn, Yuri; Pardalos, Panos M.: Graph clustering via intra-cluster density maximization (2020)
  2. Micheletti, Sandro M. R.: Quintessence and Tachyon dark energy in interaction with dark matter: observational constraints and model selection (2020)
  3. Moreno, Sebastián; Pereira, Jordi; Yushimito, Wilfredo: A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution (2020)
  4. Pan, Yuangang; Tsang, Ivor W.; Singh, Avinash K.; Lin, Chin-Teng; Sugiyama, Masashi: Stochastic multichannel ranking with brain dynamics preferences (2020)
  5. Porth, C. Brock; Porth, Lysa; Zhu, Wenjun; Boyd, Milton; Tan, Ken Seng; Liu, Kai: Remote sensing applications for insurance: a predictive model for pasture yield in the presence of systemic weather (2020)
  6. Rabinowicz, Assaf; Rosset, Saharon: Assessing prediction error at interpolation and extrapolation points (2020)
  7. Reichl, Johannes: Estimating marginal likelihoods from the posterior draws through a geometric identity (2020)
  8. Rosset, Saharon; Tibshirani, Ryan J.: From fixed-X to random-X regression: bias-variance decompositions, covariance penalties, and prediction error estimation (2020)
  9. Sang, Peijun; Cao, Jiguo: Functional single-index quantile regression models (2020)
  10. Schnaubelt, Matthias; Fischer, Thomas G.; Krauss, Christopher: Separating the signal from the noise -- financial machine learning for Twitter (2020)
  11. Schrangl, P.; Giarré, L.: On optimal design of experiments for static polynomial approximation of nonlinear systems (2020)
  12. Shan, Qianqian; Hong, Yili; Meeker, William Q.: Seasonal warranty prediction based on recurrent event data (2020)
  13. Sheng, Baohuai; Liu, Huanxiang; Wang, Huimin: Learning rates for the kernel regularized regression with a differentiable strongly convex loss (2020)
  14. Shen, Jieli; Liu, Regina Y.; Xie, Min-ge: (i)Fusion: individualized fusion learning (2020)
  15. Torrecilla, José L.; Ramos-Carreño, Carlos; Sánchez-Montañés, Manuel; Suárez, Alberto: Optimal classification of Gaussian processes in homo- and heteroscedastic settings (2020)
  16. Voelkel, Michael A.; Sachs, Anna-Lena; Thonemann, Ulrich W.: An aggregation-based approximate dynamic programming approach for the periodic review model with random yield (2020)
  17. Wager, Stefan: Cross-validation, risk estimation, and model selection: comment on a paper by Rosset and Tibshirani (2020)
  18. Winkler, Joab R.; Mitrouli, Marilena: Condition estimation for regression and feature selection (2020)
  19. Wu, Yufei; Yu, Guan: Weighted linear programming discriminant analysis for high-dimensional binary classification (2020)
  20. Yang, Yuehan; Zhu, Ji: A two-step method for estimating high-dimensional Gaussian graphical models (2020)

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