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)
Online Learning with Set-valued Feedback
COLT 2024
Online Structured Prediction with Fenchel–Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss
COLT 2024
OnlineTAS: An Online Baseline for Temporal Action Segmentation
NeurIPS 2024
On Measuring Faithfulness or Self-consistency of Natural Language Explanations
ACL 2024
On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint)
IJCAI 2024
On Parameter Estimation in Deviated Gaussian Mixture of Experts
AISTATS 2024
On provable privacy vulnerabilities of graph representations
NeurIPS 2024
On Regularized Radon-Nikodym Differentiation
JMLR 2024
On Socially Fair Low-Rank Approximation and Column Subset Selection
NeurIPS 2024
On Softmax Direct Preference Optimization for Recommendation
NeurIPS 2024
On Sparse Canonical Correlation Analysis
NeurIPS 2024
On Sufficient Graphical Models
JMLR 2024
On Tail Decay Rate Estimation of Loss Function Distributions
JMLR 2024
On the Ability of Developers' Training Data Preservation of Learnware
NeurIPS 2024
On the Adversarial Robustness of Benjamini Hochberg
NeurIPS 2024
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
AAAI 2024
On the Calibration of Human Pose Estimation
ICML 2024
On the calibration of powerset speaker diarization models
Interspeech 2024
On the cohesion and separability of average-link for hierarchical agglomerative clustering
NeurIPS 2024
On the Comparison between Multi-modal and Single-modal Contrastive Learning
NeurIPS 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing
JMLR 2024
On the Computational Complexity of Private High-dimensional Model Selection
NeurIPS 2024
On the Concept Trustworthiness in Concept Bottleneck Models
AAAI 2024
On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods
JMLR 2024
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
CVPR 2024