Learning Theory

High probability generalization bounds for uniformly stable algorithms with nearly optimal rate COLT 2019 How do infinite width bounded norm networks look in function space? COLT 2019 How Do Neural Networks See Depth in Single Images? ICCV 2019 How Hard is Robust Mean Estimation? COLT 2019 How Powerful are Graph Neural Networks? ICLR 2019 How Well Do Machines Perform on IQ tests: a Comparison Study on a Large-Scale Dataset IJCAI 2019 Hypothesis Set Stability and Generalization NeurIPS 2019 Implicit Regularization of Accelerated Methods in Hilbert Spaces NeurIPS 2019 Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks NeurIPS 2019 Improved Generalization Bounds for Robust Learning ALT 2019 Improved Regret Bounds for Bandit Combinatorial Optimization NeurIPS 2019 Improving Generalization and Stability of Generative Adversarial Networks ICLR 2019 Incorporating Label Dependencies in Multilabel Stance Detection EMNLP 2019 Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits NeurIPS 2019 Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates NeurIPS 2019 Initialization of ReLUs for Dynamical Isometry NeurIPS 2019 Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets NAACL 2019 Intrinsic dimension of data representations in deep neural networks NeurIPS 2019 Is Deeper Better only when Shallow is Good? NeurIPS 2019 Iterative Classroom Teaching AAAI 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NeurIPS 2019 Latent Structure Models for Natural Language Processing ACL 2019 LCA: Loss Change Allocation for Neural Network Training NeurIPS 2019 Learnability of Solutions to Conjunctive Queries JMLR 2019 Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers NeurIPS 2019