overparameterized neural network

DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks AISTATS 2021 Does Preprocessing Help Training Over-parameterized Neural Networks? NeurIPS 2021 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances ICML 2021 Gradient Starvation: A Learning Proclivity in Neural Networks NeurIPS 2021 Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks COLT 2021 One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks AISTATS 2021 Overparameterisation and worst-case generalisation: friend or foe? ICLR 2021 **Paper retracted by author request (see pdf for retraction notice from the authors)** Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping COLT 2021 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network AISTATS 2021 The Dynamics of Gradient Descent for Overparametrized Neural Networks L4DC 2021 The Implicit Bias of Minima Stability: A View from Function Space NeurIPS 2021 Distributionally Robust Neural Networks ICLR 2020 Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology NeurIPS 2020 Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks AISTATS 2020 Kernel and Rich Regimes in Overparametrized Models COLT 2020 On the Similarity between the Laplace and Neural Tangent Kernels NeurIPS 2020 Small Data, Big Decisions: Model Selection in the Small-Data Regime ICML 2020 Convergence of Adversarial Training in Overparametrized Neural Networks NeurIPS 2019 Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks NeurIPS 2019 Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks ICML 2019 Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers NeurIPS 2019 On Lazy Training in Differentiable Programming NeurIPS 2019 On Learning Over-parameterized Neural Networks: A Functional Approximation Perspective NeurIPS 2019 Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NeurIPS 2018