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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)

Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm NeurIPS 2023 Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning AAAI 2023 Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD AAAI 2023 Stability Guarantees for Feature Attributions with Multiplicative Smoothing NeurIPS 2023 Stability of Random Forests and Coverage of Random-Forest Prediction Intervals NeurIPS 2023 Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds NeurIPS 2023 Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints NeurIPS 2023 Stabilizing GANs’ Training with Brownian Motion Controller ICML 2023 Stable Learning via Sparse Variable Independence AAAI 2023 Stable Nonconvex-Nonconcave Training via Linear Interpolation NeurIPS 2023 Stable Target Field for Reduced Variance Score Estimation in Diffusion Models ICLR 2023 STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection CVPR 2023 StarryNet: Empowering Researchers to Evaluate Futuristic Integrated Space and Terrestrial Networks NSDI 2023 State and parameter learning with PARIS particle Gibbs ICML 2023 State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory NeurIPS 2023 Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks NeurIPS 2023 Statistical and Computational Limits for Tensor-on-Tensor Association Detection COLT 2023 Statistical and Computational Trade-off in Multi-Agent Multi-Armed Bandits NeurIPS 2023 Statistical Comparisons of Classifiers by Generalized Stochastic Dominance JMLR 2023 Statistical-Computational Tradeoffs in Mixed Sparse Linear Regression COLT 2023 Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings EMNLP 2023 Statistical Efficiency of Score Matching: The View from Isoperimetry ICLR 2023 Statistical Foundations of Prior-Data Fitted Networks ICML 2023 Statistical Guarantees for Consensus Clustering ICLR 2023 Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory NeurIPS 2023