Optimization

Two-Player Games for Efficient Non-Convex Constrained Optimization ALT 2019 Two-Timescale Networks for Nonlinear Value Function Approximation ICLR 2019 Uncovering Specific-Shape Graph Anomalies in Attributed Graphs AAAI 2019 Understanding and correcting pathologies in the training of learned optimizers ICML 2019 Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation ICML 2019 Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets ICLR 2019 Understanding the Impact of Entropy on Policy Optimization ICML 2019 Understanding the Role of Momentum in Stochastic Gradient Methods NeurIPS 2019 Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition Interspeech 2019 Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions ICLR 2019 UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization NeurIPS 2019 Unsupervised Alignment of Embeddings with Wasserstein Procrustes AISTATS 2019 Unsupervised Feature Selection by Pareto Optimization AAAI 2019 Unsupervised Image Matching and Object Discovery as Optimization CVPR 2019 Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity IJCAI 2019 Using Benson’s Algorithm for Regularization Parameter Tracking AAAI 2019 Using Large Corpus N-gram Statistics to Improve Recurrent Neural Language Models NAACL 2019 Using Statistics to Automate Stochastic Optimization NeurIPS 2019 Value-based Search in Execution Space for Mapping Instructions to Programs NAACL 2019 Variance-based Regularization with Convex Objectives JMLR 2019 Variance Reduced Policy Evaluation with Smooth Function Approximation NeurIPS 2019 Variance Reduction for Matrix Games NeurIPS 2019 Variance Reduction in Bipartite Experiments through Correlation Clustering NeurIPS 2019 Variance reduction properties of the reparameterization trick AISTATS 2019 Variational Autoencoders Pursue PCA Directions (by Accident) CVPR 2019