relu network

Learning Distributions Generated by Single-Layer ReLU Networks in the Presence of Arbitrary Outliers NeurIPS 2022 Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks JMLR 2022 Neural Network Architecture Beyond Width and Depth NeurIPS 2022 Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization ICML 2022 On Margin Maximization in Linear and ReLU Networks NeurIPS 2022 On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias NeurIPS 2022 On the Symmetries of Deep Learning Models and their Internal Representations NeurIPS 2022 Quantile regression with ReLU Networks: Estimators and minimax rates JMLR 2022 The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program ICLR 2022 The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning AAAI 2022 The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions ICLR 2022 The Separation Capacity of Random Neural Networks JMLR 2022 Training invariances and the low-rank phenomenon: beyond linear networks ICLR 2022 Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent JMLR 2022 Understanding the Evolution of Linear Regions in Deep Reinforcement Learning NeurIPS 2022 Vanishing Curvature in Randomly Initialized Deep ReLU Networks AISTATS 2022 Width is Less Important than Depth in ReLU Neural Networks COLT 2022 Adversarial Examples in Multi-Layer Random ReLU Networks NeurIPS 2021 A Modular Analysis of Provable Acceleration via Polyak’s Momentum: Training a Wide ReLU Network and a Deep Linear Network ICML 2021 An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence NeurIPS 2021 Approximating Lipschitz continuous functions with GroupSort neural networks AISTATS 2021 Deep Networks and the Multiple Manifold Problem ICLR 2021 DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis IJCAI 2021 Early-stopped neural networks are consistent NeurIPS 2021 Efficiently Learning One Hidden Layer ReLU Networks From Queries NeurIPS 2021