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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)

Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation ICLR 2024 Unbiased Estimator for Distorted Conics in Camera Calibration CVPR 2024 Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection CVPR 2024 Uncertainty-aware Action Decoupling Transformer for Action Anticipation CVPR 2024 Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting AISTATS 2024 Uncertainty-Aware GAN for Single Image Super Resolution AAAI 2024 Uncertainty Aware Learning for Language Model Alignment ACL 2024 Uncertainty-Aware Mean Opinion Score Prediction Interspeech 2024 Uncertainty-Aware Reward-Free Exploration with General Function Approximation ICML 2024 Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions NeurIPS 2024 Uncertainty Estimation by Density Aware Evidential Deep Learning ICML 2024 Uncertainty Estimation in Instance Segmentation With Star-Convex Shapes WACV 2024 Uncertainty Estimation in Large Language Models to Support Biodiversity Conservation NAACL 2024 Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission NAACL 2024 Uncertainty for Active Learning on Graphs ICML 2024 Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference L4DC 2024 Uncertainty in Language Models: Assessment through Rank-Calibration EMNLP 2024 Uncertainty quantification and robustification of model-based controllers using conformal prediction L4DC 2024 Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation AAAI 2024 Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution AAAI 2024 Uncertainty Quantification for In-Context Learning of Large Language Models NAACL 2024 Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear Model AAAI 2024 Uncertainty quantification of set-membership estimation in control and perception: Revisiting the minimum enclosing ellipsoid L4DC 2024 Uncertainty Quantification via Stable Distribution Propagation ICLR 2024 Uncertainty Regularized Evidential Regression AAAI 2024