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)
Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation
COLING 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again
NeurIPS 2022
OMLT: Optimization & Machine Learning Toolkit
JMLR 2022
On Acceleration for Convex Composite Minimization with Noise-Corrupted Gradients and Approximate Proximal Mapping
JMLR 2022
On Almost Sure Convergence Rates of Stochastic Gradient Methods
COLT 2022
On A Mallows-type Model For (Ranked) Choices
NeurIPS 2022
On Batch Teaching with Sample Complexity Bounded by VCD
NeurIPS 2022
On Biased Stochastic Gradient Estimation
JMLR 2022
On characterizations of learnability with computable learners
COLT 2022
On Collective Robustness of Bagging Against Data Poisoning
ICML 2022
On Combining Bags to Better Learn from Label Proportions
AISTATS 2022
On Computing Probabilistic Explanations for Decision Trees
NeurIPS 2022
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems
JMLR 2022
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
NeurIPS 2022
On Convergence of Gradient Descent Ascent: A Tight Local Analysis
ICML 2022
On Convergence of Lookahead in Smooth Games
AISTATS 2022
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds
NeurIPS 2022
On-Demand Sampling: Learning Optimally from Multiple Distributions
NeurIPS 2022
On-Device Training Under 256KB Memory
NeurIPS 2022
On Distributed Adaptive Optimization with Gradient Compression
ICLR 2022
On Distributionally Robust Optimization and Data Rebalancing
AISTATS 2022
On Divergence Measures for Bayesian Pseudocoresets
NeurIPS 2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation
AISTATS 2022
On Efficient Online Imitation Learning via Classification
NeurIPS 2022
One Gradient Frank-Wolfe for Decentralized Online
Convex and Submodular Optimization
ACML 2022