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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 and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method IJCAI 2022 Scalable Bayesian Network Structure Learning with Splines PGM 2022 Scalable Computation of Causal Bounds ICML 2022 Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation ICML 2022 Scalable Gaussian-process regression and variable selection using Vecchia approximations JMLR 2022 Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes ICML 2022 Scalable ML Methods to Optimize KPIs in Real-World Manufacturing Processes IJCAI 2022 Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation ICLR 2022 Scalable Sampling for Nonsymmetric Determinantal Point Processes ICLR 2022 Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions NeurIPS 2022 Scalable Spike-and-Slab ICML 2022 Scaled ReLU Matters for Training Vision Transformers AAAI 2022 Scale-free Unconstrained Online Learning for Curved Losses COLT 2022 Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion AISTATS 2022 Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements JMLR 2022 Scaling Gaussian Process Optimization by Evaluating a Few Unique Candidates Multiple Times ICML 2022 Scaling Laws from the Data Manifold Dimension JMLR 2022 Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments EMNLP 2022 Scaling Structured Inference with Randomization ICML 2022 Scaling Up Influence Functions AAAI 2022 SCALoss: Side and Corner Aligned Loss for Bounding Box Regression AAAI 2022 ScePT: Scene-Consistent, Policy-Based Trajectory Predictions for Planning CVPR 2022 Scheduling with Untrusted Predictions IJCAI 2022 Score-Based Generative Modeling with Critically-Damped Langevin Diffusion ICLR 2022 Score-Based Generative Models Detect Manifolds NeurIPS 2022