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)
Online Planning in POMDPs with Self-Improving Simulators
IJCAI 2022
Online Search with Best-Price and Query-Based Predictions
AAAI 2022
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
ICLR 2022
Online Task Assignment Problems with Reusable Resources
AAAI 2022
Online Training Through Time for Spiking Neural Networks
NeurIPS 2022
On Low-rank Trace Regression under General Sampling Distribution
JMLR 2022
Only tails matter: Average-Case Universality and Robustness in the Convex Regime
ICML 2022
On Margin Maximization in Linear and ReLU Networks
NeurIPS 2022
On Margins and Derandomisation in PAC-Bayes
AISTATS 2022
On Margins and Generalisation for Voting Classifiers
NeurIPS 2022
On Measuring Causal Contributions via do-interventions
ICML 2022
On Measuring Excess Capacity in Neural Networks
NeurIPS 2022
On Mixup Regularization
JMLR 2022
On Multimarginal Partial Optimal Transport: Equivalent Forms and Computational Complexity
AISTATS 2022
On Non-local Convergence Analysis of Deep Linear Networks
ICML 2022
On Non-Random Missing Labels in Semi-Supervised Learning
ICLR 2022
On Numerical Integration in Neural Ordinary Differential Equations
ICML 2022
On Optimal Learning Under Targeted Data Poisoning
NeurIPS 2022
On PAC-Bayesian reconstruction guarantees for VAEs
AISTATS 2022
On PAC Learning Halfspaces in Non-interactive Local
Privacy Model with Public Unlabeled Data
ACML 2022
On Predicting Generalization using GANs
ICLR 2022
On provably robust meta-Bayesian optimization
UAI 2022
On Redundancy and Diversity in Cell-based Neural Architecture Search
ICLR 2022
On Regularized Square-root Regression Problems: Distributionally Robust Interpretation and Fast Computations
JMLR 2022
On reporting scores and agreement for error annotation tasks
EMNLP 2022