linear neural network

Optimal criterion for feature learning of two-layer linear neural network in high dimensional interpolation regime ICLR 2024 Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks NeurIPS 2024 Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks NeurIPS 2024 Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence AISTATS 2024 The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis JMLR 2024 Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network NeurIPS 2023 The Implicit Regularization of Momentum Gradient Descent in Overparametrized Models AAAI 2023 The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks JMLR 2022 A unifying view on implicit bias in training linear neural networks ICLR 2021 Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data NeurIPS 2021 Representation Costs of Linear Neural Networks: Analysis and Design NeurIPS 2021 Unique Properties of Flat Minima in Deep Networks ICML 2020 A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks ICLR 2019 Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks NeurIPS 2019 On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization ICML 2018 How regularization affects the critical points in linear networks NeurIPS 2017