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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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'25

Papers (including subtopics)

Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration JMLR 2022 Towards Practical Control of Singular Values of Convolutional Layers NeurIPS 2022 Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias NeurIPS 2022 Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation NeurIPS 2022 Towards Robust and Reproducible Active Learning Using Neural Networks CVPR 2022 Towards Robust Dense Retrieval via Local Ranking Alignment IJCAI 2022 Towards Scaling Difference Target Propagation by Learning Backprop Targets ICML 2022 Towards Statistical and Computational Complexities of Polyak Step Size Gradient Descent AISTATS 2022 Towards Theoretical Analysis of Transformation Complexity of ReLU DNNs ICML 2022 Towards Theoretically Grounded Evolutionary Learning IJCAI 2022 Towards Theoretically Inspired Neural Initialization Optimization NeurIPS 2022 Towards Understanding Biased Client Selection in Federated Learning AISTATS 2022 Towards Understanding Generalization via Decomposing Excess Risk Dynamics ICLR 2022 Towards Understanding Grokking: An Effective Theory of Representation Learning NeurIPS 2022 Towards understanding how momentum improves generalization in deep learning ICML 2022 Towards Understanding Sharpness-Aware Minimization ICML 2022 Towards Understanding the Condensation of Neural Networks at Initial Training NeurIPS 2022 Towards Understanding the Mixture-of-Experts Layer in Deep Learning NeurIPS 2022 Towards Understanding the Robustness Against Evasion Attack on Categorical Data ICLR 2022 Towards Unified Representations of Knowledge Graph and Expert Rules for Machine Learning and Reasoning AACL 2022 Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective JMLR 2022 Toward Zero Oracle Word Error Rate on the Switchboard Benchmark Interspeech 2022 TPC: Transformation-Specific Smoothing for Point Cloud Models ICML 2022 TPU-GAN: Learning temporal coherence from dynamic point cloud sequences ICLR 2022 Trace norm regularization for multi-task learning with scarce data COLT 2022