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)
OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting
AAAI 2020
On 1/n neural representation and robustness
NeurIPS 2020
On Adaptivity in Information-Constrained Online Learning
AAAI 2020
On Application of Bayesian Parametric and Non-parametric Methods for User Cohorting in Product Search
ACL 2020
On Approximate Thompson Sampling with Langevin Algorithms
ICML 2020
On casting importance weighted autoencoder to an EM algorithm to learn deep generative models
AISTATS 2020
On Computation and Generalization of Generative Adversarial Imitation Learning
ICLR 2020
On Conditional Versus Marginal Bias in Multi-Armed Bandits
ICML 2020
O(n) Connections are Expressive Enough: Universal Approximability of Sparse Transformers
NeurIPS 2020
On Contrastive Learning for Likelihood-free Inference
ICML 2020
On Convergence and Generalization of Dropout Training
NeurIPS 2020
On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
ICML 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond
JMLR 2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations
NeurIPS 2020
On Coresets for Regularized Regression
ICML 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions
NeurIPS 2020
On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
ICML 2020
One-Bit Compressed Sensing via One-Shot Hard Thresholding
UAI 2020
On Efficiency in Hierarchical Reinforcement Learning
NeurIPS 2020
On Efficient Adjustment in Causal Graphs
JMLR 2020
On Efficient Constructions of Checkpoints
ICML 2020
On Efficient Low Distortion Ultrametric Embedding
ICML 2020
One Sample Stochastic Frank-Wolfe
AISTATS 2020
One-shot Distributed Ridge Regression in High Dimensions
ICML 2020
One-Shot Neural Architecture Search via Novelty Driven Sampling
IJCAI 2020