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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)

Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach ICLR 2023 Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters ICCV 2023 Domain Generalization via Balancing Training Difficulty and Model Capability ICCV 2023 Domain Generalization via Rationale Invariance ICCV 2023 Domain Specified Optimization for Deployment Authorization ICCV 2023 Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic Modeling EACL 2023 Do Not Marginalize Mechanisms, Rather Consolidate! NeurIPS 2023 Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks ICML 2023 Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models NeurIPS 2023 Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy NeurIPS 2023 Don’t Predict Counterfactual Values, Predict Expected Values Instead AAAI 2023 Don’t waste a single annotation: improving single-label classifiers through soft labels EMNLP 2023 DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining NeurIPS 2023 DOT: A Distillation-Oriented Trainer ICCV 2023 Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control NeurIPS 2023 Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023 Double Duality: Variational Primal-Dual Policy Optimization for Constrained Reinforcement Learning JMLR 2023 Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage NeurIPS 2023 Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee NeurIPS 2023 Double-Weighting for Covariate Shift Adaptation ICML 2023 Doubly Robust Augmented Transfer for Meta-Reinforcement Learning NeurIPS 2023 Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence JMLR 2023 Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction IJCAI 2023 DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method NeurIPS 2023 DP-BART for Privatized Text Rewriting under Local Differential Privacy ACL 2023