%0 Conference Paper %1 schreiter2016efficient %A Schreiter, Jens %A Nguyen-Tuong, Duy %A Toussaint, Marc %B Advances in artificial neural networks, machine learning and computational intelligence : selected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015) %C Amsterdam %D 2016 %E Kanevski, Mikhail %E Herault, Romain %E Aiolli, Fabio %E Bunte, Kerstin %I Elsevier %K %N 192 %P 29-37 %R 10.1016/j.neucom.2016.02.032 %T Efficient sparsification for Gaussian process regression

@inproceedings{schreiter2016efficient, added-at = {2023-08-31T16:42:48.000+0200}, address = {Amsterdam}, affiliation = {Schreiter, J (Reprint Author), Robert Bosch GmbH, Corp Sect Res & Adv Engn, Cognit Syst Grp, D-70465 Stuttgart, Germany. Schreiter, Jens; Duy Nguyen-Tuong, Robert Bosch GmbH, Corp Sect Res & Adv Engn, Cognit Syst Grp, D-70465 Stuttgart, Germany. Schreiter, Jens; Toussaint, Marc, Univ Stuttgart, Inst Parallel & Distributed Syst, Machine Learning & Robot Lab, D-70569 Stuttgart, Germany.}, author = {Schreiter, Jens and Nguyen-Tuong, Duy and Toussaint, Marc}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/22ae39aa5b19d60be2eec44d2fae36c29/puma-wartung}, booktitle = {Advances in artificial neural networks, machine learning and computational intelligence : selected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015)}, doi = {10.1016/j.neucom.2016.02.032}, editor = {Kanevski, Mikhail and Herault, Romain and Aiolli, Fabio and Bunte, Kerstin}, eventdate = {2015-04-22/2015-04-24}, eventtitle = {23rd European Symposium on Artificial Neural Networks (ESANN)}, interhash = {dd936463c7d9b28a8e8989d7b3eb9a3f}, intrahash = {2ae39aa5b19d60be2eec44d2fae36c29}, keywords = {}, language = {eng}, number = 192, pages = {29-37}, publisher = {Elsevier}, research-areas = {Computer Science}, series = {Neurocomputing}, timestamp = {2023-08-31T14:42:48.000+0200}, title = {Efficient sparsification for Gaussian process regression}, unique-id = {ISI:000375629000004}, venue = {Bruges, Belgium}, year = 2016 }