Journal of Machine Learning Research, Volume 1

Volume 1, 2000

• Marina Meila, Michael I. Jordan:
  Learning with Mixtures of Trees. 1-48
  
• David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie:
  Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. 49-75
  
• Justin A. Boyan, Andrew W. Moore:
  Learning Evaluation Functions to Improve Optimization by Local Search. 77-112
  
• Erin L. Allwein, Robert E. Schapire, Yoram Singer:
  Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. 113-141
  

Volume 1, 2001

• Ronan Collobert, Samy Bengio:
  SVMTorch: Support Vector Machines for Large-Scale Regression Problems. 143-160
  
• Olvi L. Mangasarian, David R. Musicant:
  Lagrangian Support Vector Machines. 161-177
  
• Alex J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson:
  Regularized Principal Manifolds. 179-209
  
• Michael E. Tipping:
  Sparse Bayesian Learning and the Relevance Vector Machine. 211-244
  
• Ralf Herbrich, Thore Graepel, Colin Campbell:
  Bayes Point Machines. 245-279
  i

• Mark Herbster, Manfred K. Warmuth:
  Tracking the Best Linear Predictor. 281-309
  
• Robert E. Mahony, Robert C. Williamson:
  Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms. 311-355