Learning Theory

Computational Separations between Sampling and Optimization NeurIPS 2019 Concentration Inequalities for Conditional Value at Risk ICML 2019 Conditions on Features for Temporal Difference-Like Methods to Converge IJCAI 2019 Connections Between Mirror Descent, Thompson Sampling and the Information Ratio NeurIPS 2019 Constraint-based Causal Structure Learning with Consistent Separating Sets NeurIPS 2019 Contextual bandits with continuous actions: Smoothing, zooming, and adapting COLT 2019 Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence NeurIPS 2019 Convergence of Gaussian Belief Propagation Under General Pairwise Factorization: Connecting Gaussian MRF with Pairwise Linear Gaussian Model JMLR 2019 Convergence of Gradient Descent on Separable Data AISTATS 2019 Correlated bandits or: How to minimize mean-squared error online ICML 2019 Correlating Neural and Symbolic Representations of Language ACL 2019 Counter-example Guided Learning of Bounds on Environment Behavior CoRL 2019 Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis NeurIPS 2019 Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds ICLR 2019 Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation NeurIPS 2019 Deep learning generalizes because the parameter-function map is biased towards simple functions ICLR 2019 Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm IJCAI 2019 Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019 Deep ReLU Networks Have Surprisingly Few Activation Patterns NeurIPS 2019 Depth Separations in Neural Networks: What is Actually Being Separated? COLT 2019 Detecting Overfitting of Deep Generative Networks via Latent Recovery CVPR 2019 Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks NeurIPS 2019 Differentially Private Learning of Geometric Concepts ICML 2019 Dimension-Free Error Bounds from Random Projections AAAI 2019 Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm COLT 2019