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
14
29
44
31
52
189
195
212
235
352
382
457
787
816
828
1,066
1,391
1,913
3,012
3,646
4,303
4,450
5,357
6,155
5,854
1,521
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
On the Power of Optimism in Constrained Online Convex Optimization
IJCAI 2025
On the Privacy-preserving Generalized Eigenvalue Problem
ACML 2025
On the Private Estimation of Smooth Transport Maps
ICML 2025
On the Provable Separation of Scales in Maximal Update Parameterization
ICML 2025
On the Query Complexity of Verifier-Assisted Language Generation
ICML 2025
On the Relation Between Fine-Tuning, Topological Properties, and Task Performance in Sense-Enhanced Embeddings
ACL 2025
On the Relation between Trainability and Dequantization of Variational Quantum Learning Models
ICLR 2025
On the Robustness of Kernel Goodness-of-Fit Tests
JMLR 2025
On the Robustness of Reward Models for Language Model Alignment
ICML 2025
On the Robustness Tradeoff in Fine-Tuning
ICCV 2025
On the Role of Label Noise in the Feature Learning Process
ICML 2025
On the Role of Unobserved Sequences on Sample-based Uncertainty Quantification for LLMs
EMNLP 2025
On the Same Wavelength? Evaluating Pragmatic Reasoning in Language Models across Broad Concepts
EMNLP 2025
On the Sample Complexity of Next-Token Prediction
AISTATS 2025
On the Statistical Mechanisms of Distributional Compositional Generalization
ICML 2025
On the Statistical Properties of Generative Adversarial Models for Low Intrinsic Data Dimension
JMLR 2025
On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
ICML 2025
On the Trainability and Classical Simulability of Learning Matrix Product States Variationally
AAAI 2025
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
ICML 2025
On the Utility of Equal Batch Sizes for Inference in Stochastic Gradient Descent
JMLR 2025
On the Vulnerability of Text Sanitization
NAACL 2025
On Tractability of Learning Bayesian Networks with Ancestral Constraints
AISTATS 2025
On Tradeoffs in Learning-Augmented Algorithms
AISTATS 2025
On Volume Minimization in Conformal Regression
ICML 2025
On Zero-Initialized Attention: Optimal Prompt and Gating Factor Estimation
ICML 2025