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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)

Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability ICML 2023 Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions NeurIPS 2023 Skip-Plan: Procedure Planning in Instructional Videos via Condensed Action Space Learning ICCV 2023 SLACK: Stable Learning of Augmentations With Cold-Start and KL Regularization CVPR 2023 SLAMB: Accelerated Large Batch Training with Sparse Communication ICML 2023 SLaM: Student-Label Mixing for Distillation with Unlabeled Examples NeurIPS 2023 SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization NeurIPS 2023 SLOG: A Structural Generalization Benchmark for Semantic Parsing EMNLP 2023 SLOTH: Structured Learning and Task-Based Optimization for Time Series Forecasting on Hierarchies AAAI 2023 Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning EMNLP 2023 Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness NeurIPS 2023 Smart Initial Basis Selection for Linear Programs ICML 2023 SMATCH++: Standardized and Extended Evaluation of Semantic Graphs EACL 2023 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023 Smoothed Analysis of Sequential Probability Assignment NeurIPS 2023 Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models NeurIPS 2023 Smoothly Giving up: Robustness for Simple Models AISTATS 2023 Smooth Non-stationary Bandits ICML 2023 SMoP: Towards Efficient and Effective Prompt Tuning with Sparse Mixture-of-Prompts EMNLP 2023 SMT Safety Verification of Ontology-Based Processes AAAI 2023 SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process ICML 2023 Social Bias Meets Data Bias: The Impacts of Labeling and Measurement Errors on Fairness Criteria AAAI 2023 SODA: Robust Training of Test-Time Data Adaptors NeurIPS 2023 SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition AAAI 2023 SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning ICLR 2023