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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)

SampleMix: A Sample-wise Pre-training Data Mixing Strategy by Coordinating Data Quality and Diversity EMNLP 2025 Sample-Optimal Agnostic Boosting with Unlabeled Data ICML 2025 Sample-specific Noise Injection for Diffusion-based Adversarial Purification ICML 2025 Sample then Identify: A General Framework for Risk Control and Assessment in Multimodal Large Language Models ICLR 2025 Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025 Sampling Binary Data by Denoising through Score Functions ICML 2025 Sampling Boundary for Causal Effect Estimation ACML 2025 Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics AISTATS 2025 Sampling From Multiscale Densities With Delayed Rejection Generalized Hamiltonian Monte Carlo AISTATS 2025 Sampling from the Random Linear Model via Stochastic Localization Up to the AMP Threshold AISTATS 2025 Sandcastles in the Storm: Revisiting the (Im)possibility of Strong Watermarking ACL 2025 SAND: One-Shot Feature Selection with Additive Noise Distortion ICML 2025 Sassha: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation ICML 2025 Satisficing Regret Minimization in Bandits ICLR 2025 SAVA: Scalable Learning-Agnostic Data Valuation ICLR 2025 ScaffoldGPT: A Scaffold-based GPT Model for Drug Optimization MLHC 2025 Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up ICML 2025 Scalability of Bayesian Network Structure Elicitation with Large Language Models: a Novel Methodology and Comparative Analysis COLING 2025 Scalable Acceleration for Classification-Based Derivative-Free Optimization AAAI 2025 Scalable and Adaptive Variational Bayes Methods for Hawkes Processes JMLR 2025 Scalable and Efficient Probabilistic Inference for Bayesian Deep Learning and Generative Modeling AAAI 2025 Scalable and Trustworthy Learning in Heterogeneous Networks AAAI 2025 Scalable Approximation Algorithms for p-Wasserstein Distance and Its Variants ICML 2025 Scalable Autoregressive Monocular Depth Estimation CVPR 2025 Scalable Bayesian Learning with posteriors ICLR 2025