Optimization

Learning Probabilistic Models: An Expected Utility Maximization Approach JMLR 2003 Learning Rates for Q-learning JMLR 2003 MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling JMLR 2003 On the Rate of Convergence of Regularized Boosting Classifiers JMLR 2003 Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning JMLR 2003 Smooth Boosting and Learning with Malicious Noise JMLR 2003 Speedup Learning for Repair-based Search by Identifying Redundant Steps JMLR 2003 The em Algorithm for Kernel Matrix Completion with Auxiliary Data JMLR 2003 Tree Induction vs. Logistic Regression: A Learning-Curve Analysis JMLR 2003 Ultraconservative Online Algorithms for Multiclass Problems JMLR 2003 Use of the Zero-Norm with Linear Models and Kernel Methods JMLR 2003 A Robust Minimax Approach to Classification JMLR 2002 Efficient Algorithms for Decision Tree Cross-validation JMLR 2002 Finding the Most Interesting Patterns in a Database Quickly by Using Sequential Sampling JMLR 2002 Learning to Construct Fast Signal Processing Implementations JMLR 2002 Minimal Kernel Classifiers JMLR 2002 On Boosting with Polynomially Bounded Distributions JMLR 2002 Optimal Structure Identification With Greedy Search JMLR 2002 Policy Search using Paired Comparisons JMLR 2002 Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels JMLR 2002 Text Chunking based on a Generalization of Winnow JMLR 2002 A New Approximate Maximal Margin Classification Algorithm JMLR 2001 Efficient SVM Training Using Low-Rank Kernel Representations JMLR 2001 Exact Simplification of Support Vector Solutions JMLR 2001 Lagrangian Support Vector Machines JMLR 2001