- Learning with Mixtures of Trees
- Marina Meila, Michael I. Jordan;
1(Oct):1-48, 2000.
[abs]
[pdf]
[ps.gz]
[ps]
[html]
|
- Dependency Networks for Inference, Collaborative Filtering, and Data Visualization
- David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Kadie;
1(Oct):49-75, 2000.
[abs]
[pdf]
[ps.gz]
[ps]
[html]
|
- Learning Evaluation Functions to Improve Optimization by Local Search
- Justin Boyan, Andrew W. Moore;
1(Nov):77-112, 2000.
[abs]
[pdf]
[ps.gz]
[ps]
|
- Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
- Erin L. Allwein, Robert E. Schapire, Yoram Singer;
1(Dec):113-141, 2000.
[abs]
[pdf]
[ps.gz]
[ps]
|
- SVMTorch: Support Vector Machines for Large-Scale Regression Problems
(Kernel Machines Section)
- Ronan Collobert, Samy Bengio;
1(Feb):143-160, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
[html]
|
- Lagrangian Support Vector Machines
(Kernel Machines Section)
- O. L. Mangasarian, David R. Musicant;
1(Mar):161-177, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
[html]
|
- Regularized Principal Manifolds
(Kernel Machines Section)
- Alexander J. Smola, Sebastian Mika, Bernhard Schölkopf, Robert C. Williamson;
1(Jun):179-209, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
|
- Sparse Bayesian Learning and the Relevance Vector Machine
- Michael E. Tipping;
1(Jun):211-244, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
|
- Bayes Point Machines
(Kernel Machines Section)
- Ralf Herbrich, Thore Graepel, Colin Campbell;
1(Aug):245-279, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
|
- Tracking the Best Linear Predictor
- Mark Herbster, Manfred K. Warmuth;
1(Sep):281-309, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
|
- Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms
- Robert E. Mahony, Robert C. Williamson;
1(Sep):311-355, 2001.
[abs]
[pdf]
[ps.gz]
[ps]
|
