weight matrix

Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization NeurIPS 2022 Spectral Tensor Train Parameterization of Deep Learning Layers AISTATS 2021 Controllable Orthogonalization in Training DNNs CVPR 2020 DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks AAAI 2020 Learning Factorized Weight Matrix for Joint Filtering ICML 2020 Learning nonlinear dynamical systems from a single trajectory L4DC 2020 Structured Pruning of Large Language Models EMNLP 2020 A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks ICLR 2019 Generalizable Adversarial Training via Spectral Normalization ICLR 2019 On Computation and Generalization of Generative Adversarial Networks under Spectrum Control ICLR 2019 Spectral Regularization for Combating Mode Collapse in GANs ICCV 2019 Stochastic Gradient Descent Learns State Equations with Nonlinear Activations COLT 2019 Traditional and Heavy Tailed Self Regularization in Neural Network Models ICML 2019 Can We Gain More from Orthogonality Regularizations in Training Deep Networks? NeurIPS 2018 Kronecker Recurrent Units ICML 2018 On orthogonality and learning recurrent networks with long term dependencies ICML 2017 Parseval Networks: Improving Robustness to Adversarial Examples ICML 2017 Multi-View Domain Generalization for Visual Recognition ICCV 2015