Parallel Gaussian process regression with low-rank covariance matrix approximations
Uncertainty in Artificial Intelligence - Proceedings of the 29th Conference, UAI 2013
Saved in:
Main Authors: | Chen, J., Cao, N., Low, K.H., Ouyang, R., Tan, C.K.-Y., Jaillet, P. |
---|---|
Other Authors: | COMPUTER SCIENCE |
Format: | Conference or Workshop Item |
Published: |
2014
|
Online Access: | http://scholarbank.nus.edu.sg/handle/10635/78277 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Gaussian Variational Approximation With a Factor Covariance Structure
by: Victor Ong, et al.
Published: (2018) -
Sparse low-rank matrix approximation for data compression
by: Hou, Junhui, et al.
Published: (2018) -
LOW-RANK MATRIX APPROXIMATION VIA MOCK-CHEBYSHEV SUBSET INTERPOLATION
by: LEE JIA QI ANDRIS
Published: (2021) -
LOW-RANK MATRIX APPROXIMATION VIA MOCK-CHEBYSHEV SUBSET INTERPOLATION
by: LEE JIA QI ANDRIS
Published: (2021) -
Gaussian process on regression
by: Lee, Kenneth Jing Wei
Published: (2023)