Optimization

Adaptive Gradient Methods with Dynamic Bound of Learning Rate ICLR 2019 Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search ICML 2019 Adaptivity and Optimality: A Universal Algorithm for Online Convex Optimization UAI 2019 AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods ICLR 2019 A Dual Approach to Verify and Train Deep Networks IJCAI 2019 A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019 A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression NeurIPS 2019 A General and Adaptive Robust Loss Function CVPR 2019 A Generic Acceleration Framework for Stochastic Composite Optimization NeurIPS 2019 Aggregated Momentum: Stability Through Passive Damping ICLR 2019 A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation NeurIPS 2019 A Margin-based Loss with Synthetic Negative Samples for Continuous-output Machine Translation EMNLP 2019 An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints NeurIPS 2019 Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization ACL 2019 A Sufficient Condition for Convergences of Adam and RMSProp CVPR 2019 A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI AAAI 2019 A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning CVPR 2019 A unified variance-reduced accelerated gradient method for convex optimization NeurIPS 2019 AutoLoss: Learning Discrete Schedule for Alternate Optimization ICLR 2019 AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks AAAI 2019 Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019 Band-limited Training and Inference for Convolutional Neural Networks ICML 2019 Beyond Gradient Descent for Regularized Segmentation Losses CVPR 2019 Calibrated Stochastic Gradient Descent for Convolutional Neural Networks AAAI 2019 Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training EMNLP 2019