Neural Network Optimization

The Implicit Bias of Gradient Descent on Separable Data JMLR 2018 The Lingering of Gradients: How to Reuse Gradients Over Time NeurIPS 2018 Theoretical Linear Convergence of Unfolded ISTA and Its Practical Weights and Thresholds NeurIPS 2018 The Spectrum of the Fisher Information Matrix of a Single-Hidden-Layer Neural Network NeurIPS 2018 Total stochastic gradient algorithms and applications in reinforcement learning NeurIPS 2018 Towards Binary-Valued Gates for Robust LSTM Training ICML 2018 Towards Effective Low-Bitwidth Convolutional Neural Networks CVPR 2018 Towards Robust Neural Machine Translation ACL 2018 Towards Two-Dimensional Sequence to Sequence Model in Neural Machine Translation EMNLP 2018 Training Deep Neural Networks with 8-bit Floating Point Numbers NeurIPS 2018 Training DNNs with Hybrid Block Floating Point NeurIPS 2018 Training Neural Networks Using Features Replay NeurIPS 2018 Training Recurrent Neural Network through Moment Matching for NLP Applications Interspeech 2018 Transfer Learning with Neural AutoML NeurIPS 2018 Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss NeurIPS 2018 Understanding and Simplifying One-Shot Architecture Search ICML 2018 Uniform Convergence of Gradients for Non-Convex Learning and Optimization NeurIPS 2018 Variance-Reduced Stochastic Gradient Descent on Streaming Data NeurIPS 2018 Visualizing the Loss Landscape of Neural Nets NeurIPS 2018 When is a Convolutional Filter Easy to Learn? ICLR 2018 Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients? NeurIPS 2018 Whispered Speech to Neutral Speech Conversion Using Bidirectional LSTMs Interspeech 2018 ZCU-NTIS Speaker Diarization System for the DIHARD 2018 Challenge Interspeech 2018 Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization NeurIPS 2018 Accelerating Stochastic Composition Optimization JMLR 2017