Generalization

Data-dependent PAC-Bayes priors via differential privacy NeurIPS 2018 Improving Text-to-SQL Evaluation Methodology ACL 2018 Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NeurIPS 2018 Multi-Class Learning: From Theory to Algorithm NeurIPS 2018 Rearranging the Familiar: Testing Compositional Generalization in Recurrent Networks EMNLP 2018 The Limits of Post-Selection Generalization NeurIPS 2018 Discriminative State Space Models NeurIPS 2017 Exploring Generalization in Deep Learning NeurIPS 2017 Information-theoretic analysis of generalization capability of learning algorithms NeurIPS 2017 Learning Low-Dimensional Metrics NeurIPS 2017 On Optimal Generalizability in Parametric Learning NeurIPS 2017 Spectrally-normalized margin bounds for neural networks NeurIPS 2017 Error Analysis of Generalized Nyström Kernel Regression NeurIPS 2016 Structured Prediction Theory Based on Factor Graph Complexity NeurIPS 2016 Algorithmic Stability and Uniform Generalization NeurIPS 2015 Generalization in Adaptive Data Analysis and Holdout Reuse NeurIPS 2015 Less is More: Nyström Computational Regularization NeurIPS 2015 Multi-class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms NeurIPS 2015 On the Optimality of Classifier Chain for Multi-label Classification NeurIPS 2015 Altitude Training: Strong Bounds for Single-Layer Dropout NeurIPS 2014 From Stochastic Mixability to Fast Rates NeurIPS 2014 The limits of squared Euclidean distance regularization NeurIPS 2014 Learning Multiple Models via Regularized Weighting NeurIPS 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013 On Flat versus Hierarchical Classification in Large-Scale Taxonomies NeurIPS 2013