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
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'15
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'25
Papers (including subtopics)
An Analysis of Quantile Temporal-Difference Learning
JMLR 2024
An Analysis of the Variance of Diffusion-based Speech Enhancement
Interspeech 2024
An Analysis of Tokenization: Transformers under Markov Data
NeurIPS 2024
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
ICLR 2024
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning
NeurIPS 2024
An Analytic Solution to Covariance Propagation in Neural Networks
AISTATS 2024
An Approximate Skolem Function Counter
AAAI 2024
An Archive Can Bring Provable Speed-ups in Multi-Objective Evolutionary Algorithms
IJCAI 2024
An Asymptotic Study of Discriminant and Vote-Averaging Schemes for Randomly-Projected Linear Discriminants
JMLR 2024
An Automatic Prompt Generation System for Tabular Data Tasks
NAACL 2024
Anchor Points: Benchmarking Models with Much Fewer Examples
EACL 2024
An Eager Satisfiability Modulo Theories Solver for Algebraic Datatypes
AAAI 2024
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering
ICML 2024
A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
NeurIPS 2024
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
ICML 2024
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise
NeurIPS 2024
An Effective Dynamic Gradient Calibration Method for Continual Learning
ICML 2024
An Effective Polynomial Technique for Compiling Conditional Effects Away
AAAI 2024
An Efficient High-dimensional Gradient Estimator for Stochastic Differential Equations
NeurIPS 2024
An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding
NeurIPS 2024
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization
AISTATS 2024
An Efficient Subgraph-Inferring Framework for Large-Scale Heterogeneous Graphs
AAAI 2024
An Efficient Tester-Learner for Halfspaces
ICLR 2024
An Embedding Framework for the Design and Analysis of Consistent Polyhedral Surrogates
JMLR 2024
An Empirical Investigation Into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification
WACV 2024