generalization error

Time-Accuracy Tradeoffs in Kernel Prediction: Controlling Prediction Quality JMLR 2017 Accurate Robust and Efficient Error Estimation for Decision Trees ICML 2016 Learnability of Non-I.I.D. ACML 2016 Regret Bounds for Non-decomposable Metrics with Missing Labels NeurIPS 2016 Semi-Supervised Learning with Adaptive Spectral Transform AISTATS 2016 Train faster, generalize better: Stability of stochastic gradient descent ICML 2016 A Market Framework for Eliciting Private Data NeurIPS 2015 An embarrassingly simple approach to zero-shot learning ICML 2015 Discriminative Robust Transformation Learning NeurIPS 2015 Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension ACML 2015 On the Optimality of Classifier Chain for Multi-label Classification NeurIPS 2015 Regularization Path of Cross-Validation Error Lower Bounds NeurIPS 2015 On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification NeurIPS 2014 PAC-Bayesian Theory for Transductive Learning AISTATS 2014 Top Rank Optimization in Linear Time NeurIPS 2014 Clustered Support Vector Machines AISTATS 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013 Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NeurIPS 2013 On Flat versus Hierarchical Classification in Large-Scale Taxonomies NeurIPS 2013 Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions ACML 2013 Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013 Local Supervised Learning through Space Partitioning NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 Plug-in Approach to Active Learning JMLR 2012 Selective Labeling via Error Bound Minimization NeurIPS 2012