Optimization

Procrastinating with Confidence: Near-Optimal, Anytime, Adaptive Algorithm Configuration NeurIPS 2019 Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal Correlations ICCV 2019 Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis ACL 2019 Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm ICCV 2019 Projection-Free Bandit Convex Optimization AISTATS 2019 Projection Free Online Learning over Smooth Sets AISTATS 2019 Projection onto Minkowski Sums with Application to Constrained Learning ICML 2019 Projections for Approximate Policy Iteration Algorithms ICML 2019 PROMT Systems for WMT 2019 Shared Translation Task ACL 2019 Protecting Elections by Recounting Ballots IJCAI 2019 Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes NeurIPS 2019 Provable Guarantees for Gradient-Based Meta-Learning ICML 2019 Provable Non-linear Inductive Matrix Completion NeurIPS 2019 Provably Accurate Double-Sparse Coding JMLR 2019 Provably Efficient Maximum Entropy Exploration ICML 2019 Provably Robust Blackbox Optimization for Reinforcement Learning CoRL 2019 Provably robust boosted decision stumps and trees against adversarial attacks NeurIPS 2019 Proximal Distance Algorithms: Theory and Practice JMLR 2019 Proximal Mean-Field for Neural Network Quantization ICCV 2019 Proximal Splitting Meets Variance Reduction AISTATS 2019 ProxQuant: Quantized Neural Networks via Proximal Operators ICLR 2019 Pushing the Range Limits of Commercial Passive RFIDs NSDI 2019 PyTorch: An Imperative Style, High-Performance Deep Learning Library NeurIPS 2019 Quasi-Globally Optimal and Efficient Vanishing Point Estimation in Manhattan World ICCV 2019 Quasi-Newton Trust Region Policy Optimization CoRL 2019