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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 Classification of G-invariant Shallow Neural Networks NeurIPS 2022 A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One JMLR 2022 A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality AISTATS 2022 A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications ICLR 2022 A Closer Look at Learned Optimization: Stability, Robustness, and Inductive Biases NeurIPS 2022 A Closer Look at Parameter Contributions When Training Neural Language and Translation Models COLING 2022 A Closer Look at Prototype Classifier for Few-shot Image Classification NeurIPS 2022 A Closer Look at Smoothness in Domain Adversarial Training ICML 2022 ACL Tutorial Proposal: Towards Reproducible Machine Learning Research in Natural Language Processing ACL 2022 A Combinatorial Perspective on the Optimization of Shallow ReLU Networks NeurIPS 2022 A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning NeurIPS 2022 A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks NeurIPS 2022 A Comparative Study of Faithfulness Metrics for Model Interpretability Methods ACL 2022 A Comparison of Hamming Errors of Representative Variable Selection Methods ICLR 2022 A Complete Characterisation of ReLU-Invariant Distributions AISTATS 2022 A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation ICML 2022 A Comprehensive Comparison of Neural Networks as Cognitive Models of Inflection EMNLP 2022 A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking NeurIPS 2022 A Computable Definition of the Spectral Bias AAAI 2022 A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension NeurIPS 2022 A Consistent and Differentiable Lp Canonical Calibration Error Estimator NeurIPS 2022 A Consistent and Efficient Evaluation Strategy for Attribution Methods ICML 2022 A consistently adaptive trust-region method NeurIPS 2022 A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction NeurIPS 2022 A Continuous Time Framework for Discrete Denoising Models NeurIPS 2022