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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Policy Certificates: Towards Accountable Reinforcement Learning ICML 2019 Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games NeurIPS 2019 Policy Poisoning in Batch Reinforcement Learning and Control NeurIPS 2019 POLITEX: Regret Bounds for Policy Iteration using Expert Prediction ICML 2019 Polynomial Cost of Adaptation for X-Armed Bandits NeurIPS 2019 Polynomial Representation for Persistence Diagram CVPR 2019 Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics AAAI 2019 POPQORN: Quantifying Robustness of Recurrent Neural Networks ICML 2019 Popularity Prediction on Online Articles with Deep Fusion of Temporal Process and Content Features AAAI 2019 PoseRBPF: A Rao-Blackwellized Particle Filter for6D Object Pose Estimation RSS 2019 Posing Fair Generalization Tasks for Natural Language Inference EMNLP 2019 Positional Encoding to Control Output Sequence Length NAACL 2019 Positive and Unlabeled Learning with Label Disambiguation IJCAI 2019 Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator ICLR 2019 Power analysis of knockoff filters for correlated designs NeurIPS 2019 PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization NeurIPS 2019 Practical and Consistent Estimation of f-Divergences NeurIPS 2019 Practical Deep Learning with Bayesian Principles NeurIPS 2019 Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning UAI 2019 Practical Obstacles to Deploying Active Learning EMNLP 2019 Practical Two-Step Lookahead Bayesian Optimization NeurIPS 2019 Precision Matrix Estimation with Noisy and Missing Data AISTATS 2019 Precision-Recall versus Accuracy and the Role of Large Data Sets AAAI 2019 Preconditioner on Matrix Lie Group for SGD ICLR 2019 Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis MLHC 2019