Theory

The Finite Model Theory of Bayesian Networks: Descriptive Complexity IJCAI 2018 The glass ceiling in NLP EMNLP 2018 The Implicit Bias of Gradient Descent on Separable Data JMLR 2018 The Limits of Post-Selection Generalization NeurIPS 2018 The Many Faces of Exponential Weights in Online Learning COLT 2018 The Multilinear Structure of ReLU Networks ICML 2018 Theoretical Analysis of Sparse Subspace Clustering with Missing Entries ICML 2018 Theoretical guarantees for EM under misspecified Gaussian mixture models NeurIPS 2018 The Pessimistic Limits and Possibilities of Margin-based Losses in Semi-supervised Learning NeurIPS 2018 The Role of Temporal Variation in Narrative Organization Interspeech 2018 The Search Problem in Mixture Models JMLR 2018 The Spectrum of the Fisher Information Matrix of a Single-Hidden-Layer Neural Network NeurIPS 2018 The Word Analogy Testing Caveat NAACL 2018 Three steps is all you need: fast, accurate, automatic scaling decisions for distributed streaming dataflows OSDI 2018 Three-Valued Semantics for Hybrid MKNF Knowledge Bases Revisited (Extended Abstract) IJCAI 2018 Thwarting Adversarial Examples: An L_0-Robust Sparse Fourier Transform NeurIPS 2018 Topological mixture estimation ICML 2018 To Understand Deep Learning We Need to Understand Kernel Learning ICML 2018 Towards a Mathematical Understanding of the Difficulty in Learning With Feedforward Neural Networks CVPR 2018 Towards Black-box Iterative Machine Teaching ICML 2018 Towards Fast Computation of Certified Robustness for ReLU Networks ICML 2018 Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation AISTATS 2018 Tropical Geometry of Deep Neural Networks ICML 2018 Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study EMNLP 2018 Understanding Deep Neural Networks with Rectified Linear Units ICLR 2018