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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)

A Solver-free Framework for Scalable Learning in Neural ILP Architectures NeurIPS 2022 A Solver + Gradient Descent Training Algorithm for Deep Neural Networks IJCAI 2022 A Sparsity-promoting Dictionary Model for Variational Autoencoders Interspeech 2022 Aspect-based Analysis of Advertising Appeals for Search Engine Advertising NAACL 2022 A spectral-based analysis of the separation between two-layer neural networks and linear methods JMLR 2022 Assessing Combinational Generalization of Language Models in Biased Scenarios AACL 2022 Assessing Digital Language Support on a Global Scale COLING 2022 Assessing Generalization of SGD via Disagreement ICLR 2022 Associated Learning: an Alternative to End-to-End Backpropagation that Works on CNN, RNN, and Transformer ICLR 2022 A Statistical Approach for Optimal Topic Model Identification JMLR 2022 A Statistical Framework for Efficient Out of Distribution Detection in Deep Neural Networks ICLR 2022 A Statistical Manifold Framework for Point Cloud Data ICML 2022 A Statistical Online Inference Approach in Averaged Stochastic Approximation NeurIPS 2022 A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration CVPR 2022 A Stochastic Bundle Method for Interpolation JMLR 2022 A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization NeurIPS 2022 A Stochastic Momentum Accelerated Quasi-Newton Method for Neural Networks (Student Abstract) AAAI 2022 A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms ICML 2022 A Strengthened Branch and Bound Algorithm for the Maximum Common (Connected) Subgraph Problem IJCAI 2022 A Structured Dictionary Perspective on Implicit Neural Representations CVPR 2022 A study on constraining Connectionist Temporal Classification for temporal audio alignment Interspeech 2022 A Study on Manual and Automatic Evaluation for Text Style Transfer: The Case of Detoxification ACL 2022 A Study on the Ramanujan Graph Property of Winning Lottery Tickets ICML 2022 Asymptotically-Optimal Gaussian Bandits with Side Observations ICML 2022 Asymptotically Optimal Locally Private Heavy Hitters via Parameterized Sketches AISTATS 2022