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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)

Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020 Scalable Belief Propagation via Relaxed Scheduling NeurIPS 2020 Scalable Calibration of Affinity Matrices from Incomplete Observations ACML 2020 Scalable Differentiable Physics for Learning and Control ICML 2020 Scalable Exact Inference in Multi-Output Gaussian Processes ICML 2020 Scalable Gaussian Process Regression Networks IJCAI 2020 Scalable Gradients for Stochastic Differential Equations AISTATS 2020 Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM ICML 2020 Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020 Scalable Nonparametric Factorization for High-Order Interaction Events AISTATS 2020 Scalable Probabilistic Matrix Factorization with Graph-Based Priors AAAI 2020 Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020 Scalar vs. mereological conceptualizations of the N-BY-N and NUM-BY-NUM adverbials COLING 2020 ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training NeurIPS 2020 Scale-Equivariant Steerable Networks ICLR 2020 Scale-Space Flow for End-to-End Optimized Video Compression CVPR 2020 Scaling Hidden Markov Language Models EMNLP 2020 Scaling up Simhash ACML 2020 Scheduled DropHead: A Regularization Method for Transformer Models EMNLP 2020 Schwa-deletion in German noun-noun compounds COLING 2020 ScopeFlow: Dynamic Scene Scoping for Optical Flow CVPR 2020 SCOP: Scientific Control for Reliable Neural Network Pruning NeurIPS 2020 Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions AISTATS 2020 SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates ICML 2020