Theory

Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability COLT 2018 Lower Bounds for Higher-Order Convex Optimization COLT 2018 Maximum Likelihood Estimation for Mixtures of Spherical Gaussians is NP-hard JMLR 2018 Mean-field theory of graph neural networks in graph partitioning NeurIPS 2018 Measuring the Intrinsic Dimension of Objective Landscapes ICLR 2018 Multinomial Logit Bandit with Linear Utility Functions IJCAI 2018 Multi-objective Contextual Bandit Problem with Similarity Information AISTATS 2018 Multi-Task Learning for Document Ranking and Query Suggestion ICLR 2018 Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NeurIPS 2018 Near-Optimal Machine Teaching via Explanatory Teaching Sets AISTATS 2018 Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions ICML 2018 Neural Networks Trained to Solve Differential Equations Learn General Representations NeurIPS 2018 Neural Segmental Hypergraphs for Overlapping Mention Recognition EMNLP 2018 Neural Tangent Kernel: Convergence and Generalization in Neural Networks NeurIPS 2018 Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency EMNLP 2018 Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling NeurIPS 2018 Nonparametric Density Estimation under Adversarial Losses NeurIPS 2018 Numerical Analysis near Singularities in RBF Networks JMLR 2018 On Concept Forgetting in Description Logics with Qualified Number Restrictions IJCAI 2018 On GANs and GMMs NeurIPS 2018 Online Bootstrap Confidence Intervals for the Stochastic Gradient Descent Estimator JMLR 2018 Online Learning: Sufficient Statistics and the Burkholder Method COLT 2018 On Neuronal Capacity NeurIPS 2018 On Q-learning Convergence for Non-Markov Decision Processes IJCAI 2018 On Statistical Optimality of Variational Bayes AISTATS 2018