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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)

Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control ICLR 2025 Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching ICML 2025 Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization JMLR 2025 Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough? ICML 2025 ADMM for Nonconvex Optimization under Minimal Continuity Assumption ICLR 2025 ADMM for Structured Fractional Minimization ICLR 2025 Advancing African-Accented English Speech Recognition: Epistemic Uncertainty-Driven Data Selection for Generalizable ASR Models ACL 2025 Advancing Community Detection with Graph Convolutional Neural Networks: Bridging Topological and Attributive Cohesion IJCAI 2025 Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations ICML 2025 Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution AAAI 2025 Advancing Out-of-Distribution Detection via Local Neuroplasticity ICLR 2025 Advancing Sequential Numerical Prediction in Autoregressive Models ACL 2025 Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation ICCV 2025 Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets ICML 2025 Adversarial Data Augmentation for Single Domain Generalization via Lyapunov Exponent-Guided Optimization ICCV 2025 Adversarial Learning Under Hybrid Perturbations for Robust Acute Lymphoblastic Leukemia Classification AAAI 2025 Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian ICML 2025 Adversarial Robust Generalization of Graph Neural Networks ICML 2025 Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees ICML 2025 Adversarial Robustness via Deformable Convolution with Stochasticity ICML 2025 Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data ICLR 2025 Adversarial Training for Graph Convolutional Networks: Stability and Generalization Analysis IJCAI 2025 Adversarial Training for Probabilistic Robustness ICCV 2025 Adversarial Training in High-Dimensional Regression: Generated Data and Neural Networks AISTATS 2025 AdversaryAI at BLP-2025 Task 2: A Think, Refine, and Generate (TriGen) System with LoRA and Self-Refinement for Code Generation AACL 2025