DMML - High Dimension Low Sample Size

References for Classification

Note to members and contributors

To make submissions of general references, please email epf@samsi.info with the journal citation in the following format:

George, E. and Foster D. (2000). Calibration and Empirical Bayes Variable Selection, Biometrika, 87:4, 731-747.

Notes:

Please also send us the pdf or ps file if it is available.
For annotated bibliography, please add your rating [1 (Good) - 5(Very Important)] and brief comments about the paper.
For software and datasets, please either send me the URL or a tar file. The zip format is also welcome.

Annotated Bibliography

Reference Comments & Rating

George, E. and Foster D. (2000). Calibration and Empirical Bayes Variable Selection, Biometrika, 87:4, 731-747 Comments: The paper does a great job at describing the whole field clearly besides providing a novel, theoretically strong and highly applicable result. Score=5

Fokoue, E. and Lin, X. (2003). On A General Framework for Efficient Dimensionality Reduction, Journal of the American Statistical Association, 96:4, 945-1009 Comments: Very helpful and detailed coverage of the topic. Presents a wide variety of interesting applications. Score=5

List of useful references

George, E. and Foster D. (2000). Calibration and Empirical Bayes Variable Selection, Biometrika, 87:4, 731-747.

Important Data Sets

Example sheet 00: PDF Example sheet 01: PDF

Example sheet 02: PDF Example sheet 03: PDF

Reference	Comments & Rating
George, E. and Foster D. (2000). Calibration and Empirical Bayes Variable Selection, Biometrika, 87:4, 731-747	Comments: The paper does a great job at describing the whole field clearly besides providing a novel, theoretically strong and highly applicable result. Score=5
Fokoue, E. and Lin, X. (2003). On A General Framework for Efficient Dimensionality Reduction, Journal of the American Statistical Association, 96:4, 945-1009	Comments: Very helpful and detailed coverage of the topic. Presents a wide variety of interesting applications. Score=5

Example sheet 00: PDF	Example sheet 01: PDF
Example sheet 02: PDF	Example sheet 03: PDF