neural network training

Efficient Proximal Mapping of the 1-path-norm of Shallow Networks ICML 2020 Fantastic Generalization Measures and Where to Find Them ICLR 2020 Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training AISTATS 2020 Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamics NeurIPS 2020 Generalization bounds for deep convolutional neural networks ICLR 2020 Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data NeurIPS 2020 Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization ICML 2020 Identifying Mislabeled Data using the Area Under the Margin Ranking NeurIPS 2020 Learning to Auto Weight: Entirely Data-Driven and Highly Efficient Weighting Framework AAAI 2020 Learning to Generate 3D Training Data Through Hybrid Gradient CVPR 2020 Long Short-Term Sample Distillation AAAI 2020 NeuReduce: Reducing Mixed Boolean-Arithmetic Expressions by Recurrent Neural Network EMNLP 2020 On the Convergence of SARAH and Beyond AISTATS 2020 On the Regularization Properties of Structured Dropout CVPR 2020 On Warm-Starting Neural Network Training NeurIPS 2020 Quantum Algorithms for Deep Convolutional Neural Networks ICLR 2020 Region Normalization for Image Inpainting AAAI 2020 Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion ICML 2020 Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer IJCAI 2020 Stochastic Loss Function AAAI 2020 Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020 The HSIC Bottleneck: Deep Learning without Back-Propagation AAAI 2020 Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-Experts NeurIPS 2020 Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation MIDL 2020 Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity ICLR 2020