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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)

DIDS: Domain Impact-aware Data Sampling for Large Language Model Training EMNLP 2025 Did Translation Models Get More Robust Without Anyone Even Noticing? ACL 2025 Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment CVPR 2025 Difference-of-submodular Bregman Divergence ICLR 2025 Differentiable Adversarial Attacks for Marked Temporal Point Processes AAAI 2025 Differentiable Causal Discovery for Latent Hierarchical Causal Models ICLR 2025 Differentiable Information Enhanced Model-Based Reinforcement Learning AAAI 2025 Differentiable Integer Linear Programming ICLR 2025 Differentiable Optimization of Similarity Scores Between Models and Brains ICLR 2025 Differentiable Quadratic Optimization For the Maximum Independent Set Problem ICML 2025 Differential-informed Sample Selection Accelerates Multimodal Contrastive Learning ICCV 2025 Differential learning kinetics govern the transition from memorization to generalization during in-context learning ICLR 2025 Differentially private algorithms for linear queries via stochastic convex optimization AISTATS 2025 Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference ICML 2025 Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies JMLR 2025 Differentially Private Kernelized Contextual Bandits AISTATS 2025 Differentially private learners for heterogeneous treatment effects ICLR 2025 Differentially private optimization for non-decomposable objective functions ICLR 2025 Differential Mamba IJCNLP 2025 Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms ICML 2025 Differential Privacy in Distributed Learning: Beyond Uniformly Bounded Stochastic Gradients AISTATS 2025 Differential Privacy Mechanisms in Neural Tangent Kernel Regression WACV 2025 Differential Privacy Under Class Imbalance: Methods and Empirical Insights ICML 2025 Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates AAAI 2025 Differentiation and Specialization of Attention Heads via the Refined Local Learning Coefficient ICLR 2025