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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

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

Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning Rate NeurIPS 2020 Recovering Causal Structures from Low-Order Conditional Independencies AAAI 2020 Recovery of Sparse Signals from a Mixture of Linear Samples ICML 2020 Recurrent Hierarchical Topic-Guided RNN for Language Generation ICML 2020 Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations NeurIPS 2020 Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking CVPR 2020 Recursively Binary Modification Model for Nested Named Entity Recognition AAAI 2020 Reducibility and Statistical-Computational Gaps from Secret Leakage COLT 2020 Reducing Adversarially Robust Learning to Non-Robust PAC Learning NeurIPS 2020 Reducing Sampling Error in Batch Temporal Difference Learning ICML 2020 Reducing Underflow in Mixed Precision Training by Gradient Scaling IJCAI 2020 Reduction and Local Search for Weighted Graph Coloring Problem AAAI 2020 Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization NeurIPS 2020 Refined bounds for algorithm configuration: The knife-edge of dual class approximability ICML 2020 Reformer-TTS: Neural Speech Synthesis with Reformer Network Interspeech 2020 Region-Adaptive Dense Network for Efficient Motion Deblurring AAAI 2020 Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020 Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems UAI 2020 Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz Losses NeurIPS 2020 Regret in Online Recommendation Systems NeurIPS 2020 Regularization of Distinct Strategies for Unsupervised Question Generation EMNLP 2020 Regularization via Structural Label Smoothing AISTATS 2020 Regularized Context Gates on Transformer for Machine Translation ACL 2020 Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models JMLR 2020 Regularized Gaussian Belief Propagation with Nodes of Arbitrary Size JMLR 2020