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 Concentration of the Minimizers of Empirical Risks
JMLR 2024
On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods
JMLR 2024
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
AISTATS 2024
On the Consistency of Kernel Methods with Dependent Observations
ICML 2024
On the Content Bias in Frechet Video Distance
CVPR 2024
On the Convergence of an Adaptive Momentum Method for Adversarial Attacks
AAAI 2024
On the Convergence of Hierarchical Federated Learning with Partial Worker Participation
UAI 2024
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
NeurIPS 2024
On the Convergence of Projected Alternating Maximization for Equitable and Optimal Transport
JMLR 2024
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
ICML 2024
On the Diminishing Returns of Width for Continual Learning
ICML 2024
On the Distance from Calibration in Sequential Prediction
COLT 2024
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
CVPR 2024
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
ICML 2024
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
ICLR 2024
On the Effect of Initialization: The Scaling Path of 2-Layer Neural Networks
JMLR 2024
On the Effect of Key Factors in Spurious Correlation: A theoretical Perspective
AISTATS 2024
On the Effect of (Near) Duplicate Subwords in Language Modelling
ACL 2024
On the Effects of Fairness to Adversarial Vulnerability
IJCAI 2024
On the Efficiency of ERM in Feature Learning
NeurIPS 2024
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
JMLR 2024
On the Expected Size of Conformal Prediction Sets
AISTATS 2024
On the Expressive Power of Tree-Structured Probabilistic Circuits
NeurIPS 2024
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks
NeurIPS 2024
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
ICLR 2024