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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)

Disjunctive Temporal Problems under Structural Restrictions AAAI 2021 Disposable Linear Bandits for Online Recommendations AAAI 2021 Dissecting Image Crops ICCV 2021 Dissecting Supervised Contrastive Learning ICML 2021 Dissecting the Aero-Acoustic Parameters of Open Articulatory Transitions Interspeech 2021 Distance-Based Regularisation of Deep Networks for Fine-Tuning ICLR 2021 Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces ICCV 2021 Distortion in Social Choice Problems: The First 15 Years and Beyond IJCAI 2021 Distributed Covariance Steering with Consensus ADMM for Stochastic Multi-Agent Systems RSS 2021 Distributed Deep Learning In Open Collaborations NeurIPS 2021 Distributed Estimation with Multiple Samples per User: Sharp Rates and Phase Transition NeurIPS 2021 Distributed Machine Learning with Sparse Heterogeneous Data NeurIPS 2021 Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent ICLR 2021 Distributed Nyström Kernel Learning with Communications ICML 2021 Distributed Principal Component Analysis with Limited Communication NeurIPS 2021 Distributed Ranking with Communications: Approximation Analysis and Applications AAAI 2021 Distributed Saddle-Point Problems Under Data Similarity NeurIPS 2021 Distributed Second Order Methods with Fast Rates and Compressed Communication ICML 2021 Distributed Zero-Order Optimization under Adversarial Noise NeurIPS 2021 Distribution Adaptive INT8 Quantization for Training CNNs AAAI 2021 Distributional Depth-Based Estimation of Object Articulation Models CoRL 2021 Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models NeurIPS 2021 Distribution Alignment: A Unified Framework for Long-Tail Visual Recognition CVPR 2021 Distributionally Robust Multilingual Machine Translation EMNLP 2021 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning AISTATS 2021