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Learning Theory

5312 directly classified papers

Papers per year

Papers

Estimation of Gradients and Coordinate Covariation in Classification JMLR 2006
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss JMLR 2006
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms JMLR 2006
Toward Attribute Efficient Learning of Decision Lists and Parities JMLR 2006
Some Discriminant-Based PAC Algorithms JMLR 2006
Sample Complexity of Policy Search with Known Dynamics NIPS 2006
Learnability and the doubling dimension NIPS 2006
A PAC-Bayes Risk Bound for General Loss Functions NIPS 2006
Prediction on a Graph with a Perceptron NIPS 2006
Fundamental Limitations of Spectral Clustering NIPS 2006
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions NIPS 2006
Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds NIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
On Transductive Regression NIPS 2006
Temporal Coding using the Response Properties of Spiking Neurons NIPS 2006
Stability of $K$-Means Clustering NIPS 2006
Active learning for misspecified generalized linear models NIPS 2006
Learning the Structure of Linear Latent Variable Models JMLR 2006
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach JMLR 2006
Superior Guarantees for Sequential Prediction and Lossless Compression via Alphabet Decomposition JMLR 2006
Learning a Hidden Hypergraph JMLR 2006
Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006
Adaptive Online Prediction by Following the Perturbed Leader JMLR 2005
Maximum Margin Algorithms with Boolean Kernels JMLR 2005
A Generalization Error for Q-Learning JMLR 2005