English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Conference Paper

Gradient Weights help Nonparametric Regressors

MPS-Authors
/persons/resource/persons84024

Kpotufe,  Samuel
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

/persons/resource/persons83823

Boularias,  Abdeslam
Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Kpotufe, S., & Boularias, A. (2013). Gradient Weights help Nonparametric Regressors. In F. Pereira, C. J. Burges, L. Bottou, & K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 25 (pp. 2861-2869). Red Hook, NY: Curran Associates, Inc. Retrieved from https://papers.nips.cc/paper/2012/hash/286674e3082feb7e5afb92777e48821f-Abstract.html.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000E-FE1B-0
Abstract
There is no abstract available