References in zbMATH (referenced in 27 articles )

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  1. Lagergren, John H.; Nardini, John T.; Lavigne, G. Michael; Rutter, Erica M.; Flores, Kevin B.: Learning partial differential equations for biological transport models from noisy spatio-temporal data (2020)
  2. Nardini, John T.; Lagergren, John H.; Hawkins-Daarud, Andrea; Curtin, Lee; Morris, Bethan; Rutter, Erica M.; Swanson, Kristin R.; Flores, Kevin B.: Learning equations from biological data with limited time samples (2020)
  3. Xie, Weijun; Deng, Xinwei: Scalable algorithms for the sparse ridge regression (2020)
  4. Thaler, Stephan; Paehler, Ludger; Adams, Nikolaus A.: Sparse identification of truncation errors (2019)
  5. Zhao, Huan; Gao, Zhenghong; Xu, Fang; Zhang, Yidian; Huang, Jiangtao: An efficient adaptive forward-backward selection method for sparse polynomial chaos expansion (2019)
  6. Zheng, Zemin; Bahadori, M. Taha; Liu, Yan; Lv, Jinchi: Scalable interpretable multi-response regression via SEED (2019)
  7. Das, Abhimanyu; Kempe, David: Approximate submodularity and its applications: subset selection, sparse approximation and dictionary selection (2018)
  8. Huang, Jian; Jiao, Yuling; Liu, Yanyan; Lu, Xiliang: A constructive approach to (L_0) penalized regression (2018)
  9. Yuan, Xiao-Tong; Li, Ping; Zhang, Tong: Gradient hard thresholding pursuit (2018)
  10. Landrieu, Loic; Obozinski, Guillaume: Cut pursuit: fast algorithms to learn piecewise constant functions on general weighted graphs (2017)
  11. Siwek, Krzysztof; Osowski, Stanisław: Data mining methods for prediction of air pollution (2016)
  12. Chang, Jing; Lee, Herbert K. H.: Variable selection via a multi-stage strategy (2015)
  13. Han, Jiuqi; Sun, Zhengya; Hao, Hongwei: (l_0)-norm based structural sparse least square regression for feature selection (2015)
  14. Temlyakov, V. N.: Greedy approximation in convex optimization (2015)
  15. Zhang, Long; Li, Kang: Forward and backward least angle regression for nonlinear system identification (2015)
  16. Baraud, Yannick; Giraud, Christophe; Huet, Sylvie: Estimator selection in the Gaussian setting (2014)
  17. Ding, Xiaobo; Li, Lexin; Zhu, Lixing: Goodness-of-fit testing-based selection for large-(p)-small-(n) problems: a two-stage ranking approach (2014)
  18. Ramirez, Alexandro D.; Paninski, Liam: Fast inference in generalized linear models via expected log-likelihoods (2014)
  19. Dupuis, Debbie J.; Victoria-Feser, Maria-Pia: Robust VIF regression with application to variable selection in large data sets (2013)
  20. Hazrati Fard, Seyed Mehdi; Hamzeh, Ali; Hashemi, Sattar: Using reinforcement learning to find an optimal set of features (2013)

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