neural network optimization

Understanding Decoupled and Early Weight Decay AAAI 2021 Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron ACML 2021 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points ICML 2021 What Causes the Test Error? Going Beyond Bias-Variance via ANOVA JMLR 2021 When Are Solutions Connected in Deep Networks? NeurIPS 2021 When Does Gradient Descent with Logistic Loss Find Interpolating Two-Layer Networks? JMLR 2021 When MAML Can Adapt Fast and How to Assist When It Cannot AISTATS 2021 Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling? ICCV 2021 You Only Look One-Level Feature CVPR 2021 A Bayesian Perspective on Training Speed and Model Selection NeurIPS 2020 Accelerating SGD with momentum for over-parameterized learning ICLR 2020 AdderNet: Do We Really Need Multiplications in Deep Learning? CVPR 2020 Adversarial Risk Bounds through Sparsity based Compression AISTATS 2020 Alleviation of Gradient Exploding in GANs: Fake Can Be Real CVPR 2020 A mathematical model for automatic differentiation in machine learning NeurIPS 2020 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth ICML 2020 An Effective Perturbation Based Semi-Supervised Learning Method for Sound Event Detection Interspeech 2020 An Empirical Investigation of Beam-Aware Training in Supertagging EMNLP 2020 An Internal Covariate Shift Bounding Algorithm for Deep Neural Networks by Unitizing Layers' Outputs CVPR 2020 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning ICML 2020 A shooting formulation of deep learning NeurIPS 2020 Assessing Local Generalization Capability in Deep Models AISTATS 2020 A Statistical Framework for Low-bitwidth Training of Deep Neural Networks NeurIPS 2020 A Theoretical Framework for Target Propagation NeurIPS 2020 Attentive Pooling with Learnable Norms for Text Representation ACL 2020