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 Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
ICML 2021
Online-Trained Upsampler for Deep Low Complexity Video Compression
ICCV 2021
Online Variational Filtering and Parameter Learning
NeurIPS 2021
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory
AAAI 2021
On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
ICML 2021
On lp-hyperparameter Learning via Bilevel Nonsmooth Optimization
JMLR 2021
Only Train Once: A One-Shot Neural Network Training And Pruning Framework
NeurIPS 2021
On Minimum Word Error Rate Training of the Hybrid Autoregressive Transducer
Interspeech 2021
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
NeurIPS 2021
On Monotonic Linear Interpolation of Neural Network Parameters
ICML 2021
On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models
AISTATS 2021
On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems
AAAI 2021
On Optimal Interpolation in Linear Regression
NeurIPS 2021
On Orthogonality Constraints for Transformers
ACL 2021
On Path Integration of Grid Cells: Group Representation and Isotropic Scaling
NeurIPS 2021
On Plasticity, Invariance, and Mutually Frozen Weights in Sequential Task Learning
NeurIPS 2021
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
AISTATS 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks
NeurIPS 2021
On Proximal Policy Optimization’s Heavy-tailed Gradients
ICML 2021
On Query-efficient Planning in MDPs under Linear Realizability of the Optimal State-value Function
COLT 2021
On Randomized Classification Layers and Their Implications in Natural Language Generation
NAACL 2021
On random kernels of residual architectures
UAI 2021
On Recovering from Modeling Errors Using Testing Bayesian Networks
ICML 2021
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
AISTATS 2021
On Robust Mean Estimation under Coordinate-level Corruption
ICML 2021