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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)

Bayesian Attention Modules NeurIPS 2020 Bayesian Bits: Unifying Quantization and Pruning NeurIPS 2020 Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks NeurIPS 2020 Bayesian Closed Surface Fitting Through Tensor Products JMLR 2020 Bayesian Decision Process for Budget-efficient Crowdsourced Clustering IJCAI 2020 Bayesian Deep Ensembles via the Neural Tangent Kernel NeurIPS 2020 Bayesian Deep Learning and a Probabilistic Perspective of Generalization NeurIPS 2020 Bayesian Differential Privacy for Machine Learning ICML 2020 Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation ICML 2020 Bayesian experimental design using regularized determinantal point processes AISTATS 2020 Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods NeurIPS 2020 Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020 Bayesian Image Classification with Deep Convolutional Gaussian Processes AISTATS 2020 Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances ICML 2020 Bayesian Learning of Probabilistic Dipole Inversion for Quantitative Susceptibility Mapping MIDL 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020 Bayesian Meta Sampling for Fast Uncertainty Adaptation ICLR 2020 Bayesian Methods for Semi-supervised Text Annotation COLING 2020 Bayesian Model Selection with Graph Structured Sparsity JMLR 2020 Bayesian Network Model Averaging Classifiers by Subbagging PGM 2020 Bayesian network structure learning with causal effects in the presence of latent variables PGM 2020 Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract) AAAI 2020 Bayesian Optimisation over Multiple Continuous and Categorical Inputs ICML 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020 Bayesian Optimization for Iterative Learning NeurIPS 2020