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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)

Going Deeper With Directly-Trained Larger Spiking Neural Networks AAAI 2021 Going Deeper With Image Transformers ICCV 2021 Good Classification Measures and How to Find Them NeurIPS 2021 Good Classifiers are Abundant in the Interpolating Regime AISTATS 2021 Goodness-of-Fit Test for Mismatched Self-Exciting Processes AISTATS 2021 Goten: GPU-Outsourcing Trusted Execution of Neural Network Training AAAI 2021 GOT: Testing for Originality in Natural Language Generation ACL 2021 GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data UAI 2021 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning ICML 2021 Gradient-Based Algorithms for Machine Teaching CVPR 2021 Gradient-based Editing of Memory Examples for Online Task-free Continual Learning NeurIPS 2021 Gradient-based Hyperparameter Optimization Over Long Horizons NeurIPS 2021 Gradient-based optimization for multi-resource spatial coverage problems UAI 2021 Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization AAAI 2021 Gradient Descent in RKHS with Importance Labeling AISTATS 2021 Gradient Descent on Neural Networks Typically Occurs at the Edge of Stability ICLR 2021 Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias NeurIPS 2021 Gradient Forward-Propagation for Large-Scale Temporal Video Modelling CVPR 2021 Gradient Methods Never Overfit On Separable Data JMLR 2021 Gradient Normalization for Generative Adversarial Networks ICCV 2021 Gradient Projection Memory for Continual Learning ICLR 2021 Gradient Regularization for Noise-Robust Speaker Verification Interspeech 2021 Gradient Starvation: A Learning Proclivity in Neural Networks NeurIPS 2021 GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training NeurIPS 2021 GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training ICML 2021