Efficient sampling for Gaussian graphical models via spectral sparsification

D Cheng, Y Cheng, Y Liu, R Peng… - … on Learning Theory, 2015 - proceedings.mlr.press
Motivated by a sampling problem basic to computational statistical inference, we develop a
toolset based on spectral sparsification for a family of fundamental problems involving …
被引用次数：43 相关文章
[PDF] mit.edu

[PDF][PDF] Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

D Cheng, Y Cheng, Y Liu, R Peng, SH Teng - jmlr.csail.mit.edu
Motivated by a sampling problem basic to computational statistical inference, we develop a
toolset based on spectral sparsification for a family of fundamental problems involving …
[PDF] archive.org

[PDF][PDF] Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

D Cheng, Y Cheng, Y Liu, R Peng, SH Teng - scholar.archive.org
Motivated by a sampling problem basic to computational statistical inference, we develop a
toolset based on spectral sparsification for a family of fundamental problems involving …

Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

D Cheng, Y Cheng, Y Liu, R Peng… - … on Learning Theory, 2015 - proceedings.mlr.press
Motivated by a sampling problem basic to computational statistical inference, we develop a
toolset based on spectral sparsification for a family of fundamental problems involving …

Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification

D Cheng, Y Cheng, Y Liu, R Peng… - Conference on Learning …, 2015 - jmlr.csail.mit.edu
Motivated by a sampling problem basic to computational statistical inference, we develop a
toolset based on spectral sparsification for a family of fundamental problems involving …