Core Methods
51,083 papers (8 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Representation Learning (22,308)
Classification (15,497)
Regression (5,281)
Clustering (3,809)
Embedding Learning (3,795)
Metric Learning (2,938)
Graph Neural Networks (1,211)
Graphical Models (1,093)
Feature Learning (891)
Kernel Methods (795)
Dimensionality Reduction (780)
Interpretability (512)
Feature Selection (511)
Matrix Factorization (408)
Ranking (315)
Ensemble Methods (300)
Support Vector Machine (295)
Anomaly Detection (281)
Sequence Modeling (244)
Structured Prediction (237)
Sequence Labeling (157)
Topic Modeling (150)
Sparse Coding (140)
Matrix Completion (131)
Neural Networks (114)
Retrieval (105)
Density Estimation (104)
Estimation (83)
Inference (56)
Decision Tree (50)
Feature Extraction (40)
Model Selection (39)
Prediction (35)
Information Extraction (7)
Papers per year
4
21
30
55
40
51
225
219
249
257
357
364
480
942
818
966
1,394
2,092
3,114
4,415
4,853
5,064
5,371
5,992
6,412
5,823
1,475
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
On the Calibration of Large Language Models and Alignment
EMNLP 2023
On the Calibration of Probabilistic Classifier Sets
AISTATS 2023
On the Capacity Limits of Privileged ERM
AISTATS 2023
On the Complexity of Bayesian Generalization
ICML 2023
On the Complexity of PAC Learning in Hilbert Spaces
AAAI 2023
On the Complexity of Representation Learning in Contextual Linear Bandits
AISTATS 2023
On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results
JMLR 2023
On the Connection Between MPNN and Graph Transformer
ICML 2023
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis
NeurIPS 2023
On the Consistency Rate of Decision Tree Learning Algorithms
AISTATS 2023
On the Convergence of CART under Sufficient Impurity Decrease Condition
NeurIPS 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation
AISTATS 2023
On the Convergence Rate of Gaussianization with Random Rotations
ICML 2023
On the Dimensionality of Sentence Embeddings
EMNLP 2023
On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.
ICLR 2023
On the Effects of Self-Supervision and Contrastive Alignment in Deep Multi-View Clustering
CVPR 2023
On the Estimation of Derivatives Using Plug-in Kernel Ridge Regression Estimators
JMLR 2023
On the Estimation of Gaussian Mixture Copula Models
ICML 2023
On the Evaluation of Neural Selective Prediction Methods for Natural Language Processing
ACL 2023
On the Exploration of Local Significant Differences For Two-Sample Test
NeurIPS 2023
On the Expressive Power of Geometric Graph Neural Networks
ICML 2023
On-the-Fly Category Discovery
CVPR 2023
On the Functional Similarity of Robust and Non-Robust Neural Representations
ICML 2023
On the Generalization of Multi-modal Contrastive Learning
ICML 2023
On the Gini-impurity Preservation For Privacy Random Forests
NeurIPS 2023