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 Generalization Analysis of Adversarial Learning
ICML 2022
On the generalization of learning algorithms that do not converge
NeurIPS 2022
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
ICLR 2022
On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model
NeurIPS 2022
On the Global Convergence Rates of Decentralized Softmax Gradient Play in Markov Potential Games
NeurIPS 2022
On the Global Optimum Convergence of Momentum-based Policy Gradient
AISTATS 2022
On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games
L4DC 2022
On the Hidden Biases of Policy Mirror Ascent in Continuous Action Spaces
ICML 2022
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
NeurIPS 2022
On the Impact of Noises in Crowd-Sourced Data for Speech Translation
ACL 2022
On the Impact of Spurious Correlation for Out-of-Distribution Detection
AAAI 2022
On the Implicit Bias of Gradient Descent for Temporal Extrapolation
AISTATS 2022
On the Importance of Firth Bias Reduction in Few-Shot Classification
ICLR 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds
NeurIPS 2022
On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games
ICML 2022
On the Impossibility of Non-trivial Accuracy in Presence of Fairness Constraints
AAAI 2022
On the inability of Gaussian process regression to optimally learn compositional functions
NeurIPS 2022
On the inductive bias of neural networks for learning read-once DNFs
UAI 2022
On the Interplay between Information Loss and Operation Loss in Representations for Classification
AISTATS 2022
On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity
NeurIPS 2022
On the Last Iterate Convergence of Momentum Methods
ALT 2022
On the Learning and Learnability of Quasimetrics
ICLR 2022
On the Learning of Non-Autoregressive Transformers
ICML 2022
On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations
NAACL 2022
On the Limitations of Stochastic Pre-processing Defenses
NeurIPS 2022