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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)

Practical Bayesian optimization in the presence of outliers AISTATS 2018 Practical Block-Wise Neural Network Architecture Generation CVPR 2018 Practical Contextual Bandits with Regression Oracles ICML 2018 Practical exact algorithm for trembling-hand equilibrium refinements in games NeurIPS 2018 Practical Methods for Graph Two-Sample Testing NeurIPS 2018 prDeep: Robust Phase Retrieval with a Flexible Deep Network ICML 2018 Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification ACML 2018 Predicting accuracy on large datasets from smaller pilot data ACL 2018 Predicting Japanese Word Order in Double Object Constructions ACL 2018 Predicting Semantic Relations using Global Graph Properties EMNLP 2018 Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model MLHC 2018 Predicting the Spatio-Temporal Evolution of Chronic Diseases in Population with Human Mobility Data IJCAI 2018 Prediction of Perceived Speech Quality Using Deep Machine Listening Interspeech 2018 Prediction Rule Reshaping ICML 2018 Predictive Approximate Bayesian Computation via Saddle Points NeurIPS 2018 PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning ICML 2018 Preference Based Adaptation for Learning Objectives NeurIPS 2018 Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018 Principled Selection of Hyperparameters in the Latent Dirichlet Allocation Model JMLR 2018 Privacy-preserving Prediction COLT 2018 Privacy Sensitive Construction of Junction Tree Agent Organization for Multiagent Graphical Models PGM 2018 Probabilistic Boolean Tensor Decomposition ICML 2018 Probabilistic Joint Face-Skull Modelling for Facial Reconstruction CVPR 2018 Probabilistic Machine Learning: Models, Algorithms and a Programming Library IJCAI 2018 Probabilistic Plant Modeling via Multi-View Image-to-Image Translation CVPR 2018