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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)

Towards Higher Pareto Frontier in Multilingual Machine Translation ACL 2023 Towards In-Distribution Compatible Out-of-Distribution Detection AAAI 2023 Towards Inference Efficient Deep Ensemble Learning AAAI 2023 Towards Inferential Reproducibility of Machine Learning Research ICLR 2023 Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning EMNLP 2023 Towards Interpreting and Utilizing Symmetry Property in Adversarial Examples AAAI 2023 Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks ICCV 2023 Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs ICLR 2023 Towards More Efficient Insertion Transformer with Fractional Positional Encoding EACL 2023 Towards One-shot Neural Combinatorial Solvers: Theoretical and Empirical Notes on the Cardinality-Constrained Case ICLR 2023 Towards Optimal Caching and Model Selection for Large Model Inference NeurIPS 2023 Towards Practical Plug-and-Play Diffusion Models CVPR 2023 Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes ICML 2023 Towards Reliable Item Sampling for Recommendation Evaluation AAAI 2023 Towards Reliable Neural Specifications ICML 2023 Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective NeurIPS 2023 Towards Robust Model Watermark via Reducing Parametric Vulnerability ICCV 2023 Towards Robustness Certification Against Universal Perturbations ICLR 2023 Towards Safe and Resilient Autonomy in Multi-Robot Systems AAAI 2023 Towards Saner Deep Image Registration ICCV 2023 Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework AISTATS 2023 Towards Scalable Coverage-Based Testing of Autonomous Vehicles CoRL 2023 Towards Sharp Analysis for Distributed Learning with Random Features IJCAI 2023 Towards Stable and Efficient Adversarial Training against l_1 Bounded Adversarial Attacks ICML 2023 Towards Stable Natural Language Understanding via Information Entropy Guided Debiasing ACL 2023