neural network optimization

BlockDrop: Dynamic Inference Paths in Residual Networks CVPR 2018 BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning CVPR 2018 ClcNet: Improving the Efficiency of Convolutional Neural Network Using Channel Local Convolutions CVPR 2018 Constructing Fast Network through Deconstruction of Convolution NeurIPS 2018 Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties ICLR 2018 Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global ICML 2018 Deep Structured Prediction with Nonlinear Output Transformations NeurIPS 2018 Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks ICML 2018 Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling EMNLP 2018 Efficient Video Object Segmentation via Network Modulation CVPR 2018 Exploring Hidden Dimensions in Accelerating Convolutional Neural Networks ICML 2018 Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis NeurIPS 2018 From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction ACL 2018 Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima ICML 2018 Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models AISTATS 2018 Hessian-based Analysis of Large Batch Training and Robustness to Adversaries NeurIPS 2018 How Does Batch Normalization Help Optimization? NeurIPS 2018 How to Start Training: The Effect of Initialization and Architecture NeurIPS 2018 Hyperparameter Optimization for Tracking With Continuous Deep Q-Learning CVPR 2018 Inference-Invariant Transformation of Batch Normalization for Domain Adaptation of Acoustic Models Interspeech 2018 Is it Time to Swish? Comparing Deep Learning Activation Functions Across NLP tasks EMNLP 2018 Kalman Normalization: Normalizing Internal Representations Across Network Layers NeurIPS 2018 Learning to Optimize Tensor Programs NeurIPS 2018 Learning to Teach with Dynamic Loss Functions NeurIPS 2018 Learning Versatile Filters for Efficient Convolutional Neural Networks NeurIPS 2018