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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)

EMT-NAS:Transferring Architectural Knowledge Between Tasks From Different Datasets CVPR 2023 Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets ICML 2023 Enabling High Quality Real-Time Communications with Adaptive Frame-Rate NSDI 2023 Enabling Team of Teams: A Trust Inference and Propagation (TIP) Model in Multi-Human Multi-Robot Teams RSS 2023 Enabling Users to Control their Internet NSDI 2023 Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity AISTATS 2023 Encoding Human Behavior in Information Design through Deep Learning NeurIPS 2023 End2End Multi-View Feature Matching with Differentiable Pose Optimization ICCV 2023 End-to-End Diffusion Latent Optimization Improves Classifier Guidance ICCV 2023 End-to-End Evaluation for Low-Latency Simultaneous Speech Translation EMNLP 2023 End-to-End Learning for Optimization via Constraint-Enforcing Approximators AAAI 2023 End-to-End Learning for Stochastic Optimization: A Bayesian Perspective ICML 2023 End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes NeurIPS 2023 End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization ICML 2023 Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models NeurIPS 2023 Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach NeurIPS 2023 Energy-Based Models for Functional Data using Path Measure Tilting AISTATS 2023 Energy-Based Test Sample Adaptation for Domain Generalization ICLR 2023 Energy Discrepancies: A Score-Independent Loss for Energy-Based Models NeurIPS 2023 Energy-Efficient Adaptive 3D Sensing CVPR 2023 Energy-Efficient Scheduling with Predictions NeurIPS 2023 Energy Guided Diffusion for Generating Neurally Exciting Images NeurIPS 2023 Energy Transformer NeurIPS 2023 Enhanced Training of Query-Based Object Detection via Selective Query Recollection CVPR 2023 Enhance Robustness of Machine Learning with Improved Efficiency AAAI 2023