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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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'25

Papers (including subtopics)

Uncertainty modeling for fine-tuned implicit functions ICLR 2025 Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations ICLR 2025 Uncertainty Modelling in Under-Represented Languages with Bayesian Deep Gaussian Processes COLING 2025 Uncertainty Propagation on LLM Agent ACL 2025 Uncertainty Unveiled: Can Exposure to More In-context Examples Mitigate Uncertainty for Large Language Models? ACL 2025 Uncertainty Weighted Gradients for Model Calibration CVPR 2025 Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models EMNLP 2025 Unconstrained Robust Online Convex Optimization ICML 2025 Uncovering Scaling Laws for Large Language Models via Inverse Problems EMNLP 2025 Underdamped Diffusion Bridges with Applications to Sampling ICLR 2025 Understanding Aggregations of Proper Learners in Multiclass Classification ALT 2025 Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron ICLR 2025 Understanding and Improving Information Preservation in Prompt Compression for LLMs EMNLP 2025 Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs EMNLP 2025 Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing ICLR 2025 Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models ICML 2025 Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination JMLR 2025 Understanding Expert Structures on Minimax Parameter Estimation in Contaminated Mixture of Experts AISTATS 2025 Understanding Factual Recall in Transformers via Associative Memories ICLR 2025 Understanding Flatness in Generative Models: Its Role and Benefits ICCV 2025 Understanding Generalization in Quantum Machine Learning with Margins ICML 2025 Understanding High-Dimensional Bayesian Optimization ICML 2025 Understanding Impact of Human Feedback via Influence Functions ACL 2025 Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality AISTATS 2025 Understanding LLM Development Through Longitudinal Study: Insights from the Open Ko-LLM Leaderboard NAACL 2025