References in zbMATH (referenced in 1225 articles , 2 standard articles )

Showing results 1 to 20 of 1225.
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  1. Ahmadi, Hesam; Shanbhag, Uday V.: On the resolution of misspecified convex optimization and monotone variational inequality problems (2020)
  2. Bachoc, François; Suvorikova, Alexandra; Ginsbourger, David; Loubes, Jean-Michel; Spokoiny, Vladimir: Gaussian processes with multidimensional distribution inputs via optimal transport and Hilbertian embedding (2020)
  3. Bain, Travaughn C.; Avila-Herrera, Juan F.; Subasi, Ersoy; Subasi, Munevver Mine: Logical analysis of multiclass data with relaxed patterns (2020)
  4. Bedoui, Adel; Lazar, Nicole A.: Bayesian empirical likelihood for ridge and Lasso regressions (2020)
  5. Binois, Mickaël; Ginsbourger, David; Roustant, Olivier: On the choice of the low-dimensional domain for global optimization via random embeddings (2020)
  6. Bisiacco, Mauro; Pillonetto, Gianluigi: Kernel absolute summability is sufficient but not necessary for RKHS stability (2020)
  7. Bourgey, Florian; De Marco, Stefano; Gobet, Emmanuel; Zhou, Alexandre: Multilevel Monte Carlo methods and lower-upper bounds in initial margin computations (2020)
  8. Buccini, Alessandro; De la Cruz Cabrera, Omar; Donatelli, Marco; Martinelli, Andrea; Reichel, Lothar: Large-scale regression with non-convex loss and penalty (2020)
  9. Canhong Wen, Aijun Zhang, Shijie Quan, Xueqin Wang: BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models (2020) not zbMATH
  10. Dobler, Dennis; Friedrich, Sarah; Pauly, Markus: Nonparametric MANOVA in meaningful effects (2020)
  11. Eftekhari, Armin; Hauser, Raphael A.: Principal component analysis by optimization of symmetric functions has no spurious local optima (2020)
  12. Fan, Jun; Xiang, Dao-Hong: Quantitative convergence analysis of kernel based large-margin unified machines (2020)
  13. Fan, Yingying; Demirkaya, Emre; Li, Gaorong; Lv, Jinchi: RANK: large-scale inference with graphical nonlinear knockoffs (2020)
  14. Flores, Hector; Villalobos, J. Rene: A stochastic planning framework for the discovery of complementary, agricultural systems (2020)
  15. Furmańczyk, Konrad; Rejchel, Wojciech: High-dimensional linear model selection motivated by multiple testing (2020)
  16. Gilman, Mikhail; Tsynkov, Semyon: Statistical characterization of scattering delay in synthetic aperture radar imaging (2020)
  17. Glaws, Andrew; Constantine, Paul G.; Cook, R. Dennis: Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments (2020)
  18. He, Xinyu; Reyes, Kristofer G.; Powell, Warren B.: Optimal learning with local nonlinear parametric models over continuous designs (2020)
  19. Janßen, Anja; Wan, Phyllis: (k)-means clustering of extremes (2020)
  20. Khan, Zardad; Gul, Asma; Perperoglou, Aris; Miftahuddin, Miftahuddin; Mahmoud, Osama; Adler, Werner; Lausen, Berthold: Ensemble of optimal trees, random forest and random projection ensemble classification (2020)

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