日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細


公開

会議論文

It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals

MPS-Authors
/persons/resource/persons85117

Rakitsch,  Barbara
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

/persons/resource/persons75313

Borgwardt,  Karsten M.
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Resource

Link
(全文テキスト(全般))

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
フルテキスト (公開)
公開されているフルテキストはありません
付随資料 (公開)
There is no public supplementary material available
引用

Rakitsch, B., Lippert, C., Borgwardt, K. M., & Stegle, O. (2013). It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. In C., Burges, L., Bottou, M., Welling, Z., Ghahramani, & K., Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (NIPS 2013) (pp. 1466-1474). Retrieved from http://papers.nips.cc/paper/5089-it-is-all-in-the-noise-efficient-multi-task-gaussian-process-inference-with-structured-residuals.


引用: https://hdl.handle.net/11858/00-001M-0000-0015-3A26-A
要旨
要旨はありません