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 Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
NeurIPS 2023
On the Consistency Rate of Decision Tree Learning Algorithms
AISTATS 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration
NeurIPS 2023
On the Convergence of AdaGrad(Norm) on R^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration
ICLR 2023
On the Convergence of Black-Box Variational Inference
NeurIPS 2023
On the Convergence of CART under Sufficient Impurity Decrease Condition
NeurIPS 2023
On the Convergence of Continual Learning with Adaptive Methods
UAI 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network
AISTATS 2023
On the Convergence of Encoder-only Shallow Transformers
NeurIPS 2023
On the Convergence of Federated Averaging with Cyclic Client Participation
ICML 2023
On the Convergence of Gradient Flow on Multi-layer Linear Models
ICML 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
AISTATS 2023
On the Convergence of SARSA with Linear Function Approximation
ICML 2023
On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size
JMLR 2023
On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
ICML 2023
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms
NeurIPS 2023
On the Correctness of Automatic Differentiation for Neural Networks with Machine-Representable Parameters
ICML 2023
On the duality between contrastive and non-contrastive self-supervised learning
ICLR 2023
On the Dynamics Under the Unhinged Loss and Beyond
JMLR 2023
On the Effectiveness of Partial Variance Reduction in Federated Learning With Heterogeneous Data
CVPR 2023
On the Effects of Structural Modeling for Neural Semantic Parsing
CoNLL 2023
On the Efficacy of Sampling Adapters
ACL 2023
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators
JMLR 2023
On the Estimation of Gaussian Mixture Copula Models
ICML 2023
On the Existence of a Complexity in Fixed Budget Bandit Identification
COLT 2023