Variable Selection Consistency of Linear Programming Discriminant Estimator
- Series
- High-Dimensional Phenomena in Statistics and Machine Learning Seminar
- Time
- Tuesday, September 9, 2014 - 15:00 for 1 hour (actually 50 minutes)
- Location
- Skiles 005
- Speaker
- Dong Xia – School of Mathematics, Georgia Tech
The linear programming discriminant(LPD) estimator is used in sparse
linear discriminant analysis for high dimensional classification
problems. In this talk we will give a sufficient condition for the
variable selection property of the LPD estimator and our result provides
optimal bound on the requirement of sample size $n$ and magnitude of
components of Bayes direction.