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15

ICML
2010
IEEE

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On Sparse Nonparametric Conditional Covariance Selection

13 years 5 months ago

On Sparse Nonparametric Conditional Covariance Selection

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We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This problem has a key role in many modern applications such as finance and computational biology. However, it has not been properly addressed. Our estimator is derived under minimal assumptions on the underlying probability distribution and works well in the high-dimensional setting. The efficiency of the algorithm is demonstrated on both simulation studies and the analysis of the stock market.

Mladen Kolar, Ankur P. Parikh, Eric P. Xing

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Conditional Covariance Selection | Conditional Precision Matrix | ICML 2010 | Machine Learning | Penalized Kernel Smoothing |

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Added	09 Nov 2010
Updated	09 Nov 2010
Type	Conference
Year	2010
Where	ICML
Authors	Mladen Kolar, Ankur P. Parikh, Eric P. Xing

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