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 f-Divergence Principled Domain Adaptation: An Improved Framework
NeurIPS 2024
On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
ICLR 2024
On a Neural Implementation of Brenier’s Polar Factorization
ICML 2024
On Bias-Variance Alignment in Deep Models
ICLR 2024
On Calibration of Speech Classification Models: Insights from Energy-Based Model Investigations
Interspeech 2024
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression
CVPR 2024
On Comparing Time- and Frequency-Domain Rhythm Measures in Classifying Assamese Dialects
Interspeech 2024
On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
ICML 2024
On Computationally Efficient Multi-Class Calibration
COLT 2024
On Convergence in Wasserstein Distance and f-divergence Minimization Problems
AISTATS 2024
On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
NeurIPS 2024
On Convergence of Incremental Gradient for Non-convex Smooth Functions
ICML 2024
On cyclical MCMC sampling
AISTATS 2024
On Differentially Private Subspace Estimation in a Distribution-Free Setting
NeurIPS 2024
On Differentially Private U Statistics
NeurIPS 2024
On Discrete Prompt Optimization for Diffusion Models
ICML 2024
On Divergence Measures for Training GFlowNets
NeurIPS 2024
On Double Descent in Reinforcement Learning with LSTD and Random Features
ICLR 2024
On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression
JMLR 2024
OneBit: Towards Extremely Low-bit Large Language Models
NeurIPS 2024
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models
JMLR 2024
On Efficient and Statistical Quality Estimation for Data Annotation
ACL 2024
On Efficiently Representing Regular Languages as RNNs
ACL 2024
One Forward is Enough for Neural Network Training via Likelihood Ratio Method
ICLR 2024
One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
NeurIPS 2024