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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)

SGD Can Converge to Local Maxima ICLR 2022 SGD with Coordinate Sampling: Theory and Practice JMLR 2022 SHAFF: Fast and consistent SHApley eFfect estimates via random Forests AISTATS 2022 Shallow and Deep Networks are Near-Optimal Approximators of Korobov Functions ICLR 2022 Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text Normalization Interspeech 2022 Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoising NeurIPS 2022 Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations AAAI 2022 Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search CVPR 2022 Sharp Analysis of Random Fourier Features in Classification AAAI 2022 Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality NeurIPS 2022 Sharp Bounds for Federated Averaging (Local SGD) and Continuous Perspective AISTATS 2022 Sharp Constants in Uniformity Testing via the Huber Statistic COLT 2022 Sharpened Quasi-Newton Methods: Faster Superlinear Rate and Larger Local Convergence Neighborhood ICML 2022 Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning NeurIPS 2022 Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods COLT 2022 Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning ICML 2022 Sharpness-Aware Minimization Improves Language Model Generalization ACL 2022 Sharpness-Aware Minimization with Dynamic Reweighting EMNLP 2022 Sharpness-Aware Training for Free NeurIPS 2022 Sharp Restricted Isometry Property Bounds for Low-Rank Matrix Recovery Problems with Corrupted Measurements AAAI 2022 ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks ICML 2022 Shifted compression framework: generalizations and improvements UAI 2022 SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models ICLR 2022 Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue ACL 2022 Shuffle Private Linear Contextual Bandits ICML 2022