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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Universal Prompt Optimizer for Safe Text-to-Image Generation NAACL 2024 Universal Rates for Active Learning NeurIPS 2024 Universal Rates for Regression: Separations between Cut-Off and Absolute Loss COLT 2024 Universal Rates of Empirical Risk Minimization NeurIPS 2024 Universal Sample Coding NeurIPS 2024 Unknown Domain Inconsistency Minimization for Domain Generalization ICLR 2024 Unlabeled Principal Component Analysis and Matrix Completion JMLR 2024 Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems NeurIPS 2024 Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND ICLR 2024 Unleashing the Potential of Large Language Models through Spectral Modulation EMNLP 2024 Unlocking Black-Box Prompt Tuning Efficiency via Zeroth-Order Optimization EMNLP 2024 Unlocking Memorization in Large Language Models with Dynamic Soft Prompting EMNLP 2024 Unlocking the Capabilities of Thought: A Reasoning Boundary Framework to Quantify and Optimize Chain-of-Thought NeurIPS 2024 Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning CVPR 2024 Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models NeurIPS 2024 Unpacking Bias: An Empirical Study of Bias Measurement Metrics, Mitigation Algorithms, and Their Interactions COLING 2024 Unraveling the Dynamics of Semi-Supervised Hate Speech Detection: The Impact of Unlabeled Data Characteristics and Pseudo-Labeling Strategies EACL 2024 Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space ICLR 2024 Unraveling the Gradient Descent Dynamics of Transformers NeurIPS 2024 Unravelling in Collaborative Learning NeurIPS 2024 Unrolled denoising networks provably learn to perform optimal Bayesian inference NeurIPS 2024 Unscrambling disease progression at scale: fast inference of event permutations with optimal transport NeurIPS 2024 UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation NeurIPS 2024 Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling IJCAI 2024 Unsupervised Deep Unrolling Networks for Phase Unwrapping CVPR 2024