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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Score-based Generative Models with Lévy Processes NeurIPS 2023 Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023 Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising ICCV 2023 SE(3) Equivariant Augmented Coupling Flows NeurIPS 2023 Searching Efficient Neural Architecture With Multi-Resolution Fusion Transformer for Appearance-Based Gaze Estimation WACV 2023 Searching for Better Database Queries in the Outputs of Semantic Parsers EACL 2023 Searching for Optimal Per-Coordinate Step-sizes with Multidimensional Backtracking NeurIPS 2023 Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation WACV 2023 Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning ICML 2023 Search-Map-Search: A Frame Selection Paradigm for Action Recognition CVPR 2023 Search Query Spell Correction with Weak Supervision in E-commerce ACL 2023 Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts CVPR 2023 Second-Order Optimization with Lazy Hessians ICML 2023 Second Order Path Variationals in Non-Stationary Online Learning AISTATS 2023 Second-order regression models exhibit progressive sharpening to the edge of stability ICML 2023 Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning AAAI 2023 SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models NeurIPS 2023 Seeing through the mess: evolutionary dynamics of lexical polysemy EMNLP 2023 SEENN: Towards Temporal Spiking Early Exit Neural Networks NeurIPS 2023 SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA EMNLP 2023 Segmented Recurrent Transformer: An Efficient Sequence-to-Sequence Model EMNLP 2023 Select and Optimize: Learning to solve large-scale TSP instances AISTATS 2023 Selection by Prediction with Conformal p-values JMLR 2023 Selective inference for k-means clustering JMLR 2023 Selective Nonparametric Regression via Testing ACML 2023