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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)

Generative Alignment of Posterior Probabilities for Source-Free Domain Adaptation WACV 2023 Generative Diffusion Prior for Unified Image Restoration and Enhancement CVPR 2023 Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transport NeurIPS 2023 Generative Pretraining for Black-Box Optimization ICML 2023 Generator Identification for Linear SDEs with Additive and Multiplicative Noise NeurIPS 2023 Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables JMLR 2023 Genetic Prompt Search via Exploiting Language Model Probabilities IJCAI 2023 GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection CVPR 2023 Geodesically convex M-estimation in metric spaces COLT 2023 GeoLS: Geodesic Label Smoothing for Image Segmentation MIDL 2023 Geometrically regularized autoencoders for non-Euclidean data ICLR 2023 Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization COLT 2023 Geometric Clifford Algebra Networks ICML 2023 GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies NeurIPS 2023 Geo-Seq2seq: Twitter User Geolocation on Noisy Data through Sequence to Sequence Learning ACL 2023 GEQ: Gaussian Kernel Inspired Equilibrium Models NeurIPS 2023 Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design NeurIPS 2023 GEX: A flexible method for approximating influence via Geometric Ensemble NeurIPS 2023 GFlowNet Foundations JMLR 2023 GFlowOut: Dropout with Generative Flow Networks ICML 2023 GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration ICML 2023 Gibbsian Polar Slice Sampling ICML 2023 GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization ICCV 2023 Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning NeurIPS 2023 GLEN: Generative Retrieval via Lexical Index Learning EMNLP 2023