Learning Theory

Decision making with limited feedback ALT 2018 Decoupling Gradient-Like Learning Rules from Representations ICML 2018 Dimension-free Information Concentration via Exp-Concavity ALT 2018 Discriminative Learning of Prediction Intervals AISTATS 2018 Distractor Generation for Multiple Choice Questions Using Learning to Rank NAACL 2018 Distribution-Specific Hardness of Learning Neural Networks JMLR 2018 Do Outliers Ruin Collaboration? ICML 2018 Dropout Training, Data-dependent Regularization, and Generalization Bounds ICML 2018 Effective Acoustic Cue Learning Is Not Just Statistical, It Is Discriminative Interspeech 2018 Efficient Contextual Bandits in Non-stationary Worlds COLT 2018 Efficient online algorithms for fast-rate regret bounds under sparsity NeurIPS 2018 Empirical Risk Landscape Analysis for Understanding Deep Neural Networks ICLR 2018 Empirical Study of the Topology and Geometry of Deep Networks CVPR 2018 Enhancing Existential Rules by Closed-World Variables IJCAI 2018 Entropy and mutual information in models of deep neural networks NeurIPS 2018 Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors ICML 2018 Escaping Saddle Points in Constrained Optimization NeurIPS 2018 Evaluating Historical Text Normalization Systems: How Well Do They Generalize? NAACL 2018 Evaluating the Ability of LSTMs to Learn Context-Free Grammars EMNLP 2018 Exploration in Structured Reinforcement Learning NeurIPS 2018 Exponential Convergence of Testing Error for Stochastic Gradient Methods COLT 2018 Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms COLT 2018 Fast generalization error bound of deep learning from a kernel perspective AISTATS 2018 Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions NeurIPS 2018 Feasible Arm Identification ICML 2018