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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)

Gait design for limbless obstacle aided locomotion using geometric mechanics RSS 2023 Game Solving with Online Fine-Tuning NeurIPS 2023 GAM: Gradient Attention Module of Optimization for Point Clouds Analysis AAAI 2023 GAN Prior Based Null-Space Learning for Consistent Super-resolution AAAI 2023 GANs as Gradient Flows that Converge JMLR 2023 Gaussian Distributed Prototypical Network for Few-shot Genomic Variant Detection ACL 2023 Gaussian processes at the Helm(holtz): A more fluid model for ocean currents ICML 2023 Gaussian Processes on Distributions based on Regularized Optimal Transport AISTATS 2023 Gaussian Processes with Errors in Variables: Theory and Computation JMLR 2023 Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients ICML 2023 gDDIM: Generalized denoising diffusion implicit models ICLR 2023 GeNAS: Neural Architecture Search with Better Generalization IJCAI 2023 Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations NeurIPS 2023 Generalization Analysis for Contrastive Representation Learning ICML 2023 Generalization and Estimation Error Bounds for Model-based Neural Networks ICLR 2023 Generalization Bounds for Adversarial Contrastive Learning JMLR 2023 Generalization Bounds for Adversarial Metric Learning IJCAI 2023 Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses ICLR 2023 Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings AAAI 2023 Generalization bounds for neural ordinary differential equations and deep residual networks NeurIPS 2023 Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels JMLR 2023 Generalization Bounds using Data-Dependent Fractal Dimensions ICML 2023 Generalization error bounds for multiclass sparse linear classifiers JMLR 2023 Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage COLT 2023 Generalization Guarantees of Self-Training of Halfspaces under Label Noise Corruption IJCAI 2023