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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)

Scalable Benchmarking and Robust Learning for Noise-Free Ego-Motion and 3D Reconstruction from Noisy Video ICLR 2025 Scalable Decentralized Algorithms for Online Personalized Mean Estimation AAAI 2025 Scalable Decentralized Learning with Teleportation ICLR 2025 Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics ICLR 2025 Scalable Equilibrium Sampling with Sequential Boltzmann Generators ICML 2025 Scalable First-order Method for Certifying Optimal k-Sparse GLMs ICML 2025 Scalable Inference for Bayesian Multinomial Logistic-Normal Dynamic Linear Models AISTATS 2025 Scalable Influence and Fact Tracing for Large Language Model Pretraining ICLR 2025 Scalable Mechanistic Neural Networks ICLR 2025 Scalable Model Merging with Progressive Layer-wise Distillation ICML 2025 Scalable Multi-Stage Influence Function for Large Language Models via Eigenvalue-Corrected Kronecker-Factored Parameterization IJCAI 2025 Scalable Private Partition Selection via Adaptive Weighting ICML 2025 Scalable Ranked Preference Optimization for Text-to-Image Generation ICCV 2025 Scalable Sobolev IPM for Probability Measures on a Graph ICML 2025 ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting ACL 2025 Scale Down to Speed Up: Dynamic Data Selection for Reinforcement Learning EMNLP 2025 Scale Efficient Training for Large Datasets CVPR 2025 Scaling Capability in Token Space: An Analysis of Large Vision Language Model JMLR 2025 Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks ICML 2025 Scaling Combinatorial Optimization Neural Improvement Heuristics with Online Search and Adaptation AAAI 2025 Scaling Data-Constrained Language Models JMLR 2025 Scaling FP8 training to trillion-token LLMs ICLR 2025 Scaling Graph-Based Dependency Parsing with Arc Vectorization and Attention-Based Refinement NAACL 2025 Scaling Inference Time Compute for Diffusion Models CVPR 2025 Scaling Laws and Efficient Inference for Ternary Language Models ACL 2025