- The Annals of Statistics 2007, Vol. 35, No. 5, 21732192
- The Entire Regularization Path for the Support Vector Machine
- Prediction by supervised principal components Trevor Hastie
- Margin trees for high-dimensional classification Robert Tibshirani
- Taxt, T., Hjort, N. & Eikvil, L. (1991), `Statistical classification using a linear mixture of multinormal probability densities', Pattern Recognition Letters 12, 731--737.
- A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning
- The Author 2006. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
- Optimal Kernel Shapes for Local Linear Regression \Lambda
- Ecological Modelling 187 (2005) 524536 Constrained ordination analysis with flexible
- The Annals of Statistics 2007, Vol. 35, No. 6, 23582364
- Statistical Science 2006, Vol. 21, No. 3, 352357
- Biometrics 65, 554563 DOI: 10.1111/j.1541-0420.2008.01116.x
- STATISTICS IN ECOLOGICAL MODELING; PRESENCE-ONLY DATA AND BOOSTED MARS
- Margin Maximizing Loss Functions Saharon Rosset, Ji Zhu and Trevor Hastie
- SOME PERSPECTIVES OF SPARSE STATISTICAL MODELING A DISSERTATION
- DISCRIMINATIVE VS INFORMATIVE LEARNING a dissertation
- 2005 Royal Statistical Society 13697412/05/67768 J. R. Statist. Soc. B (2005)
- Automatic Smoothing Spline Projection Charles B. Roosen
- TOPICS IN REGULARIZATION AND BOOSTING a dissertation
- Logistic Response Projection Pursuit CHARLES B. ROOSEN
- JSS Journal of Statistical Software March 2011, Volume 39, Issue 5. http://www.jstatsoft.org/
- Feature Extraction and Dimension Reduction with Applications to Classification
- MODELING IMAGE SEQUENCES, WITH PARTICULAR APPLICATION TO FMRI DATA
- Genomewide Association Analysis by Lasso Penalized Logistic Regression
- GENERALIZED LINEAR MODELS WITH REGULARIZATION A DISSERTATION
- Supplementary Materials to "SparseNet: Coordinate Descent with Non-Convex Penalties"
- -logb(lambda, base=2) 0 5 10 15 20
- Biostatistics (2011), 0, 0, pp. 116 doi:10.1093/biostatistics/kxr012
- November 2002 Trevor Hastie, Stanford Statistics 1 Independent Component Analysis
- -norm Support Vector Machines Ji Zhu, Saharon Rosset, Trevor Hastie, Rob Tibshirani
- Average Expression -2 -1 0 1 2
- BL EWS NB RMS -3 -2 -1 0 1 2 3
- http://smm.sagepub.com/ Statistical Methods in Medical Research
- Principal component models for sparse functional data GARETH M. JAMES
- 50 SMOOTHING IN DETAIL 50 CV curves
- Clustering methods for the analysis of DNA microarray data
- Bayesian Back tting Trevor Hastie
- MAJORITY VOTE CLASSIFIERS: THEORY AND APPLICATIONS
- A New Multiclass Generalization of AdaBoost Department of Statistics
- Discussion of Boosting Papers Jerome Friedman Trevor Hastie Saharon Rosset
- The Graphical Lasso: New Insights and Alternatives Rahul Mazumder
- Statistical Models for Image Sequences Neil Crellin, Trevor Hastie and Iain Johnstone
- Journal of Machine Learning Research 11 (2010) 2287-2322 Submitted 7/09; Revised 4/10; Published 8/10 Spectral Regularization Algorithms for Learning Large Incomplete
- Exact Covariance Thresholding into Connected Components for large-scale Graphical Lasso
