Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting NeurIPS 2023 SCADE: NeRFs from Space Carving With Ambiguity-Aware Depth Estimates CVPR 2023 Scalable Batch-Mode Deep Bayesian Active Learning via Equivalence Class Annealing ICLR 2023 Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023 Scalable Causal Discovery with Score Matching CLeaR 2023 Scalable Computation of Causal Bounds JMLR 2023 Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health AAAI 2023 Scalable Deep Kernel Gaussian Process for Vehicle Dynamics in Autonomous Racing CoRL 2023 Scalable Distributed Massive MIMO Baseband Processing NSDI 2023 Scalable high-dimensional Bayesian varying coefficient models with unknown within-subject covariance JMLR 2023 Scalable marked point processes for exchangeable and non-exchangeable event sequences AISTATS 2023 Scalable Membership Inference Attacks via Quantile Regression NeurIPS 2023 Scalable nonparametric Bayesian learning for dynamic velocity fields UAI 2023 Scalable Optimal Margin Distribution Machine IJCAI 2023 Scalable Optimal Multiway-Split Decision Trees with Constraints AAAI 2023 Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice JMLR 2023 Scalable Performance Analysis for Vision-Language Models ACL 2023 Scalable Real-Time Recurrent Learning Using Columnar-Constructive Networks JMLR 2023 Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation ICML 2023 Scalable Subset Sampling with Neural Conditional Poisson Networks ICLR 2023 Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel ICLR 2023 Scale-Invariant Infinite Hierarchical Topic Model ACL 2023 Scale Invariant Power Iteration JMLR 2023 Scaling Forward Gradient With Local Losses ICLR 2023 Scaling in Cognitive Modelling: a Multilingual Approach to Human Reading Times ACL 2023