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 Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks
AISTATS 2023
On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
ICML 2023
On the Optimality of Misspecified Kernel Ridge Regression
ICML 2023
On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure
JMLR 2023
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
NeurIPS 2023
On the Overlooked Structure of Stochastic Gradients
NeurIPS 2023
On the Pareto Front of Multilingual Neural Machine Translation
NeurIPS 2023
On the Performance of Temporal Difference Learning With Neural Networks
ICLR 2023
On the Power of Foundation Models
ICML 2023
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
ICML 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning
ICML 2023
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
NeurIPS 2023
On the Relation between Sensitivity and Accuracy in In-Context Learning
EMNLP 2023
On the Relationship Between Relevance and Conflict in Online Social Link Recommendations
NeurIPS 2023
On The Relative Error of Random Fourier Features for Preserving Kernel Distance
ICLR 2023
On the Representational Capacity of Recurrent Neural Language Models
EMNLP 2023
On the Reuse Bias in Off-Policy Reinforcement Learning
IJCAI 2023
On the Robustness of Mechanism Design under Total Variation Distance
NeurIPS 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations
ICML 2023
On the Robustness of Removal-Based Feature Attributions
NeurIPS 2023
On the Robustness of Text Vectorizers
ICML 2023
On the Role of Attention in Prompt-tuning
ICML 2023
On the Role of Entanglement and Statistics in Learning
NeurIPS 2023
On the Role of Generalization in Transferability of Adversarial Examples
UAI 2023
On the role of model uncertainties in Bayesian optimisation
UAI 2023