1. Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination

   • Yoshua Bengio
   • Dale Schuurmans

   Introduction Pages: 5 - 7

2. Model Selection for Small Sample Regression

   • Olivier Chapelle
   • Vladimir Vapnik
   • Yoshua Bengio

   OriginalPaper Pages: 9 - 23

3. Theoretical and Experimental Evaluation of the Subspace Information Criterion

   • Masashi Sugiyama
   • Hidemitsu Ogawa

   OriginalPaper Pages: 25 - 50

4. Metric-Based Methods for Adaptive Model Selection and Regularization

   • Dale Schuurmans
   • Finnegan Southey

   OriginalPaper Pages: 51 - 84

5. Model Selection and Error Estimation

   • Peter L. Bartlett
   • Stéphane Boucheron
   • Gábor Lugosi

   OriginalPaper Pages: 85 - 113

6. Statistical Properties and Adaptive Tuning of Support Vector Machines

   • Yi Lin
   • Grace Wahba
   • Yoonkyung Lee

   OriginalPaper Pages: 115 - 136

7. Structural Modelling with Sparse Kernels

   • S.R. Gunn
   • J.S. Kandola

   OriginalPaper Pages: 137 - 163

8. Kernel Matching Pursuit

   • Pascal Vincent
   • Yoshua Bengio

   OriginalPaper Pages: 165 - 187

9. Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces

   • Gunnar Rätsch
   • Ayhan Demiriz
   • Kristin P. Bennett

   OriginalPaper Pages: 189 - 218

10. On the Existence of Linear Weak Learners and Applications to Boosting

    • Shie Mannor
    • Ron Meir

    OriginalPaper Pages: 219 - 251

11. Logistic Regression, AdaBoost and Bregman Distances

    • Michael Collins
    • Robert E. Schapire
    • Yoram Singer

    OriginalPaper Pages: 253 - 285

12. Estimating Generalization Error on Two-Class Datasets Using Out-of-Bag Estimates

    • Tom Bylander

    OriginalPaper Pages: 287 - 297

13. Bayesian Treed Models

    • Hugh A. Chipman
    • Edward I. George
    • Robert E. McCulloch

    OriginalPaper Pages: 299 - 320

14. Decision Region Connectivity Analysis: A Method for Analyzing High-Dimensional Classifiers

    • Ofer Melnik

    OriginalPaper Pages: 321 - 351