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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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'25

Papers (including subtopics)

The Importance of Human-Labeled Data in the Era of LLMs IJCAI 2023 The Influence of Dimensions on the Complexity of Computing Decision Trees AAAI 2023 The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks ICLR 2023 The KFIoU Loss for Rotated Object Detection ICLR 2023 The Lauritzen-Chen Likelihood For Graphical Models AISTATS 2023 The Learnability of In-Context Learning NeurIPS 2023 The Lie Derivative for Measuring Learned Equivariance ICLR 2023 The Lie-Group Bayesian Learning Rule AISTATS 2023 The Linearity of the Effect of Surprisal on Reading Times across Languages EMNLP 2023 The Many Faces of Adversarial Machine Learning AAAI 2023 The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data NeurIPS 2023 The neural dynamics of word recognition and integration EMNLP 2023 The noise level in linear regression with dependent data NeurIPS 2023 The Numerical Stability of Hyperbolic Representation Learning ICML 2023 The One-Inclusion Graph Algorithm is not Always Optimal COLT 2023 The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes ICLR 2023 The Optimal Approximation Factors in Misspecified Off-Policy Value Function Estimation ICML 2023 The OPUS-MT Dashboard – A Toolkit for a Systematic Evaluation of Open Machine Translation Models ACL 2023 The Ordered Matrix Dirichlet for State-Space Models AISTATS 2023 Theoretical Analysis of the Inductive Biases in Deep Convolutional Networks NeurIPS 2023 Theoretical and Numerical Analysis of 3D Reconstruction Using Point and Line Incidences ICCV 2023 Theoretical and Practical Perspectives on what Influence Functions Do NeurIPS 2023 Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning ICLR 2023 Theoretical Conditions and Empirical Failure of Bracket Counting on Long Sequences with Linear Recurrent Networks EACL 2023 Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting ICML 2023