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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)

Optimistic Exploration even with a Pessimistic Initialisation ICLR 2020 Optimistic Policy Optimization with Bandit Feedback ICML 2020 Optimization and Analysis of the pAp@k Metric for Recommender Systems ICML 2020 Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural Networks NeurIPS 2020 Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions NeurIPS 2020 Optimization from Structured Samples for Coverage Functions ICML 2020 Optimization Learning: Perspective, Method, and Applications IJCAI 2020 Optimization Theory for ReLU Neural Networks Trained with Normalization Layers ICML 2020 Optimized Score Transformation for Fair Classification AISTATS 2020 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning ICML 2020 Optimizing Black-box Metrics with Adaptive Surrogates ICML 2020 Optimizing Data Usage via Differentiable Rewards ICML 2020 Optimizing Dynamic Structures with Bayesian Generative Search ICML 2020 Optimizing for the Future in Non-Stationary MDPs ICML 2020 Optimizing Influenza Vaccine Composition: From Predictions to Prescriptions MLHC 2020 Optimizing Millions of Hyperparameters by Implicit Differentiation AISTATS 2020 Optimizing Mode Connectivity via Neuron Alignment NeurIPS 2020 Optimizing Neural Networks via Koopman Operator Theory NeurIPS 2020 Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains AAAI 2020 Optimizing Rank-Based Metrics With Blackbox Differentiation CVPR 2020 Optimizing the Feature Selection Process for Better Accuracy in Datasets with a Large Number of Features (Student Abstract) AAAI 2020 Optimizing Word Segmentation for Downstream Task EMNLP 2020 Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020 OptSLA: an Optimization-Based Approach for Sequential Label Aggregation EMNLP 2020 Oracle Efficient Private Non-Convex Optimization ICML 2020