Optimization

Parameter-free, Dynamic, and Strongly-Adaptive Online Learning ICML 2020 Partial AUC Optimisation Using Recurrent Neural Networks for Music Detection with Limited Training Data Interspeech 2020 Partial Weight Adaptation for Robust DNN Inference CVPR 2020 Peeking Behind the Ordinal Curtain: Improving Distortion via Cardinal Queries AAAI 2020 PeerNomination: Relaxing Exactness for Increased Accuracy in Peer Selection IJCAI 2020 Performant TCP for Low-Power Wireless Networks NSDI 2020 PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications OSDI 2020 Pivot-based Maximal Biclique Enumeration IJCAI 2020 Planning with General Objective Functions: Going Beyond Total Rewards NeurIPS 2020 Policy Search by Target Distribution Learning for Continuous Control AAAI 2020 Position-based Scaled Gradient for Model Quantization and Pruning NeurIPS 2020 Positive Unlabeled Learning with Class-prior Approximation IJCAI 2020 Posterior Re-calibration for Imbalanced Datasets NeurIPS 2020 Practical Quasi-Newton Methods for Training Deep Neural Networks NeurIPS 2020 Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations ICLR 2020 Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods AAAI 2020 Predictive Coding for Locally-Linear Control ICML 2020 Price of Fairness in Budget Division and Probabilistic Social Choice AAAI 2020 Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm NeurIPS 2020 Principled learning method for Wasserstein distributionally robust optimization with local perturbations ICML 2020 Probabilistic Linear Solvers for Machine Learning NeurIPS 2020 Progressive Boundary Refinement Network for Temporal Action Detection AAAI 2020 Projection-Based Constrained Policy Optimization ICLR 2020 Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method NeurIPS 2020 Projective Preferential Bayesian Optimization ICML 2020