References in zbMATH (referenced in 15 articles )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Erway, Jennifer B.; Griffin, Joshua; Marcia, Roummel F.; Omheni, Riadh: Trust-region algorithms for training responses: machine learning methods using indefinite Hessian approximations (2020)
  2. Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em: Physics-informed neural networks for high-speed flows (2020)
  3. Rohan Anand, Joeran Beel: Auto-Surprise: An Automated Recommender-System (AutoRecSys) Library with Tree of Parzens Estimator (TPE) Optimization (2020) arXiv
  4. Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov, Mani Srivastava: MANGO: A Python Library for Parallel Hyperparameter Tuning (2020) arXiv
  5. Ariafar, Setareh; Coll-Font, Jaume; Brooks, Dana; Dy, Jennifer: ADMMBO: Bayesian optimization with unknown constraints using ADMM (2019)
  6. Mariappan, Ragunathan; Rajan, Vaibhav: Deep collective matrix factorization for augmented multi-view learning (2019)
  7. Aggarwal, Charu C.: Neural networks and deep learning. A textbook (2018)
  8. Chan, Shing; Elsheikh, Ahmed H.: A machine learning approach for efficient uncertainty quantification using multiscale methods (2018)
  9. Kordík, Pavel; Černý, Jan; Frýda, Tomáš: Discovering predictive ensembles for transfer learning and meta-learning (2018)
  10. Li, Lisha; Jamieson, Kevin; DeSalvo, Giulia; Rostamizadeh, Afshin; Talwalkar, Ameet: Hyperband: a novel bandit-based approach to hyperparameter optimization (2018)
  11. Bernd Bischl, Jakob Richter, Jakob Bossek, Daniel Horn, Janek Thomas, Michel Lang: mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions (2017) arXiv
  12. Mısır, Mustafa; Sebag, Michèle: \textscAlors: an algorithm recommender system (2017)
  13. Yamane, Ikko; Sasaki, Hiroaki; Sugiyama, Masashi: Regularized multitask learning for multidimensional log-density gradient estimation (2016)
  14. Krueger, Tammo; Panknin, Danny; Braun, Mikio: Fast cross-validation via sequential testing (2015)
  15. Schulz, Hannes; Cho, Kyunghyun; Raiko, Tapani; Behnke, Sven: Two-layer contractive encodings for learning stable nonlinear features (2015)