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Classification

15,805 papers

Papers per year

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Papers

AdaBoost is Consistent NIPS 2006
Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods NIPS 2006
Simplifying Mixture Models through Function Approximation NIPS 2006
Sparse Representation for Signal Classification NIPS 2006
Prediction on a Graph with a Perceptron NIPS 2006
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models NIPS 2006
Fast Discriminative Visual Codebooks using Randomized Clustering Forests NIPS 2006
Learning on Graph with Laplacian Regularization NIPS 2006
An Oracle Inequality for Clipped Regularized Risk Minimizers NIPS 2006
Large Margin Component Analysis NIPS 2006
Learning with Hypergraphs: Clustering, Classification, and Embedding NIPS 2006
Max-margin classification of incomplete data NIPS 2006
Large Margin Hidden Markov Models for Automatic Speech Recognition NIPS 2006
A PAC-Bayes Risk Bound for General Loss Functions NIPS 2006
Large Scale Hidden Semi-Markov SVMs NIPS 2006
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NIPS 2006
Statistical Comparisons of Classifiers over Multiple Data Sets JMLR 2006
Incremental Algorithms for Hierarchical Classification JMLR 2006
Generalized Bradley-Terry Models and Multi-Class Probability Estimates JMLR 2006
Some Discriminant-Based PAC Algorithms JMLR 2006
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006
A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006
Learning Minimum Volume Sets JMLR 2006
Some Theory for Generalized Boosting Algorithms JMLR 2006
QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines JMLR 2006