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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)

Learning Chaos In A Linear Way ICLR 2025 Learning Classifiers That Induce Markets ICML 2025 Learning Complexity of Gradient Descent and Conjugate Gradient Algorithms AAAI 2025 Learning Compositional Functions with Transformers from Easy-to-Hard Data COLT 2025 Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction ICML 2025 Learning Configurations for Data-Driven Multi-Objective Optimization ICML 2025 Learning Constant-Depth Circuits in Malicious Noise Models COLT 2025 Learning Continually by Spectral Regularization ICLR 2025 Learning Curves of Stochastic Gradient Descent in Kernel Regression ICML 2025 Learning curves theory for hierarchically compositional data with power-law distributed features ICML 2025 Learning Deep Dissipative Dynamics AAAI 2025 Learning Deployable Locomotion Control via Differentiable Simulation CoRL 2025 Learning Distances from Data with Normalizing Flows and Score Matching ICML 2025 Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning ICLR 2025 Learning DNF through Generalized Fourier Representations COLT 2025 Learning Dynamical Coupled Operator For High-dimensional Black-box Partial Differential Equations IJCAI 2025 Learning Dynamics in Continual Pre-Training for Large Language Models ICML 2025 Learning dynamics in linear recurrent neural networks ICML 2025 Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability ICLR 2025 Learning Dynamics of LLM Finetuning ICLR 2025 Learning Dynamics under Environmental Constraints via Measurement-Induced Bundle Structures ICML 2025 Learning-enabled Polynomial Lyapunov Function Synthesis via High-Accuracy Counterexample-Guided Framework CVPR 2025 Learning Extrapolative Sequence Transformations from Markov Chains ICML 2025 Learning Extremely High Density Crowds as Active Matters CVPR 2025 Learning Few-Step Diffusion Models by Trajectory Distribution Matching ICCV 2025