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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)

Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation NeurIPS 2023 MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates NeurIPS 2023 M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation ICLR 2023 MMD Aggregated Two-Sample Test JMLR 2023 MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability NeurIPS 2023 MMNMT: Modularizing Multilingual Neural Machine Translation with Flexibly Assembled MoE and Dense Blocks EMNLP 2023 MMVC: Learned Multi-Mode Video Compression With Block-Based Prediction Mode Selection and Density-Adaptive Entropy Coding CVPR 2023 Mnemonist: Locating Model Parameters that Memorize Training Examples UAI 2023 Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM NeurIPS 2023 Moccasin: Efficient Tensor Rematerialization for Neural Networks ICML 2023 Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder NeurIPS 2023 Modality-Agnostic Variational Compression of Implicit Neural Representations ICML 2023 Mode-constrained Model-based Reinforcement Learning via Gaussian Processes AISTATS 2023 Model-agnostic Measure of Generalization Difficulty ICML 2023 Model Analysis & Evaluation for Ambiguous Question Answering ACL 2023 Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning NeurIPS 2023 Model-based Causal Bayesian Optimization ICLR 2023 Model-Based Offline Reinforcement Learning with Local Misspecification AAAI 2023 Model-Based Offline Weighted Policy Optimization (Student Abstract) AAAI 2023 Model-Based Reinforcement Learning with Multinomial Logistic Function Approximation AAAI 2023 Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms NeurIPS 2023 Model-Based Uncertainty in Value Functions AISTATS 2023 Model-based Validation as Probabilistic Inference L4DC 2023 Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning ICML 2023 Model Calibration in Dense Classification with Adaptive Label Perturbation ICCV 2023