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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)

Learning Partial Equivariances From Data NeurIPS 2022 Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study L4DC 2022 Learning Predictions for Algorithms with Predictions NeurIPS 2022 Learning Probabilistic Models from Generator Latent Spaces with Hat EBM NeurIPS 2022 Learning Proposals for Practical Energy-Based Regression AISTATS 2022 Learning Prototype-oriented Set Representations for Meta-Learning ICLR 2022 Learning Pruning-Friendly Networks via Frank-Wolfe: One-Shot, Any-Sparsity, And No Retraining ICLR 2022 Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training JMLR 2022 Learning Representation from Neural Fisher Kernel with Low-rank Approximation ICLR 2022 Learning Revenue-Maximizing Auctions With Differentiable Matching AISTATS 2022 Learning Reversible Symplectic Dynamics L4DC 2022 Learning Sampling Distributions for Model Predictive Control CoRL 2022 Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs ICLR 2022 Learning single-index models with shallow neural networks NeurIPS 2022 Learning soft interventions in complex equilibrium systems UAI 2022 Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance AAAI 2022 Learning sparse features can lead to overfitting in neural networks NeurIPS 2022 Learning Sparse Fixed-Structure Gaussian Bayesian Networks AISTATS 2022 Learning sparse representations of preferences within Choquet expected utility theory UAI 2022 Learning Stochastic Shortest Path with Linear Function Approximation ICML 2022 Learning Strides in Convolutional Neural Networks ICLR 2022 Learning Structured Gaussians To Approximate Deep Ensembles CVPR 2022 Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models JMLR 2022 Learning the Beauty in Songs: Neural Singing Voice Beautifier ACL 2022 Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks ICLR 2022