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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)

Curriculum Reinforcement Learning via Constrained Optimal Transport ICML 2022 CVaR-Regret Bounds for Multi-armed Bandits ACML 2022 C-VTON: Context-Driven Image-Based Virtual Try-On Network WACV 2022 Cycle Consistent Probability Divergences Across Different Spaces AISTATS 2022 DAdaQuant: Doubly-adaptive quantization for communication-efficient Federated Learning ICML 2022 DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation CVPR 2022 DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization NeurIPS 2022 DALE: Differential Accumulated Local Effects for efficient and accurate global explanations ACML 2022 DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks WACV 2022 Darts: User-Friendly Modern Machine Learning for Time Series JMLR 2022 Data augmentation in Bayesian neural networks and the cold posterior effect UAI 2022 Data Cartography for Low-Resource Neural Machine Translation EMNLP 2022 Data Contamination: From Memorization to Exploitation ACL 2022 Data dependent randomized smoothing UAI 2022 Data-Derived Weak Universal Consistency JMLR 2022 DATA: Domain-Aware and Task-Aware Self-Supervised Learning CVPR 2022 Data-Driven Conditional Robust Optimization NeurIPS 2022 Data-driven Control of Unknown Linear Systems via Quantized Feedback L4DC 2022 Data-Driven Offline Optimization for Architecting Hardware Accelerators ICLR 2022 Data-Efficient Augmentation for Training Neural Networks NeurIPS 2022 Data-Efficient Backdoor Attacks IJCAI 2022 Data-Efficient Structured Pruning via Submodular Optimization NeurIPS 2022 Datamodels: Understanding Predictions with Data and Data with Predictions ICML 2022 Data sampling affects the complexity of online SGD over dependent data UAI 2022 Data Scaling Laws in NMT: The Effect of Noise and Architecture ICML 2022