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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)

Scalable Ultrafast Almost-optimal Euclidean Shortest Paths IJCAI 2024 Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport ICML 2024 ScaLearn: Simple and Highly Parameter-Efficient Task Transfer by Learning to Scale ACL 2024 Scaled Conjugate Gradient Method for Nonconvex Optimization in Deep Neural Networks JMLR 2024 Scale-free Adversarial Reinforcement Learning COLT 2024 Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models NeurIPS 2024 Scaling Convex Neural Networks with Burer-Monteiro Factorization ICLR 2024 Scaling Exponents Across Parameterizations and Optimizers ICML 2024 ScalingFilter: Assessing Data Quality through Inverse Utilization of Scaling Laws EMNLP 2024 Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement ICLR 2024 Scaling Law for Time Series Forecasting NeurIPS 2024 Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models EMNLP 2024 Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations NeurIPS 2024 Scaling Laws for Associative Memories ICLR 2024 Scaling Laws for Data Filtering-- Data Curation cannot be Compute Agnostic CVPR 2024 Scaling Laws for Fact Memorization of Large Language Models EMNLP 2024 Scaling laws for learning with real and surrogate data NeurIPS 2024 Scaling Laws for Linear Complexity Language Models EMNLP 2024 Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms NeurIPS 2024 Scaling Laws for the Value of Individual Data Points in Machine Learning ICML 2024 Scaling Laws in Linear Regression: Compute, Parameters, and Data NeurIPS 2024 Scaling Laws of Decoder-Only Models on the Multilingual Machine Translation Task EMNLP 2024 Scaling Laws of Synthetic Images for Model Training ... for Now CVPR 2024 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies NeurIPS 2024 Scaling Parameter-Constrained Language Models with Quality Data EMNLP 2024