Generalization

Dimensionality Dependent PAC-Bayes Margin Bound NeurIPS 2012 Generalization Bounds for Domain Adaptation NeurIPS 2012 Learning Multiple Tasks using Shared Hypotheses NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 Selective Labeling via Error Bound Minimization NeurIPS 2012 A Two-Stage Weighting Framework for Multi-Source Domain Adaptation NeurIPS 2011 Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss NeurIPS 2011 k-NN Regression Adapts to Local Intrinsic Dimension NeurIPS 2011 Unifying Framework for Fast Learning Rate of Non-Sparse Multiple Kernel Learning NeurIPS 2011 Learning Bounds for Importance Weighting NeurIPS 2010 On the Theory of Learnining with Privileged Information NeurIPS 2010 Permutation Complexity Bound on Out-Sample Error NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NeurIPS 2009 Human Rademacher Complexity NeurIPS 2009 Regularized Distance Metric Learning:Theory and Algorithm NeurIPS 2009 On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization NeurIPS 2008 Rademacher Complexity Bounds for Non-I.I.D. Processes NeurIPS 2008 Risk Bounds for Randomized Sample Compressed Classifiers NeurIPS 2008 Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning NeurIPS 2008 Learning Bounds for Domain Adaptation NeurIPS 2007 Stability Bounds for Non-i.i.d. Processes NeurIPS 2007 Analysis of Representations for Domain Adaptation NeurIPS 2006 An Oracle Inequality for Clipped Regularized Risk Minimizers NeurIPS 2006 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006