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 Power and Limitations of Examples for Description Logic Concepts
IJCAI 2024
On the Power of Small-size Graph Neural Networks for Linear Programming
NeurIPS 2024
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
ICLR 2024
On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX
AISTATS 2024
On the Provable Advantage of Unsupervised Pretraining
ICLR 2024
On the Relationship between Skill Neurons and Robustness in Prompt Tuning
COLING 2024
On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning
ACL 2024
On the Robustness of Editing Large Language Models
EMNLP 2024
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
NeurIPS 2024
On the Role of Attention Masks and LayerNorm in Transformers
NeurIPS 2024
On the Role of General Function Approximation in Offline Reinforcement Learning
ICLR 2024
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
NeurIPS 2024
On the Role of Server Momentum in Federated Learning
AAAI 2024
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
JMLR 2024
On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
ICML 2024
On the sample complexity of parameter estimation in logistic regression with normal design
COLT 2024
On the sample complexity of privately learning half-spaces
ACML 2024
On the Sample Complexity of Two-Layer Networks: Lipschitz Vs. Element-Wise Lipschitz Activation
ALT 2024
On the Saturation Effects of Spectral Algorithms in Large Dimensions
NeurIPS 2024
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
ICLR 2024
On the Scalability of Diffusion-based Text-to-Image Generation
CVPR 2024
On the Scaling Laws of Geographical Representation in Language Models
COLING 2024
On the Second-Order Convergence of Biased Policy Gradient Algorithms
ICML 2024
On the Sparsity of the Strong Lottery Ticket Hypothesis
NeurIPS 2024
On the Stability and Generalization of Meta-Learning
NeurIPS 2024