conftrace_

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)

Learning Coordinate Covariances via Gradients JMLR 2006 Learning Dense 3D Correspondence NeurIPS 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006 Learning from Multiple Sources NeurIPS 2006 Learning Image Components for Object Recognition JMLR 2006 Learning Minimum Volume Sets JMLR 2006 Learning Motion Style Synthesis from Perceptual Observations NeurIPS 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006 Learning on Graph with Laplacian Regularization NeurIPS 2006 Learning Parts-Based Representations of Data JMLR 2006 Learning Sparse Representations by Non-Negative Matrix Factorization and Sequential Cone Programming JMLR 2006 Learning Spectral Clustering, With Application To Speech Separation JMLR 2006 Learning Structural Equation Models for fMRI NeurIPS 2006 Learning to Detect and Classify Malicious Executables in the Wild JMLR 2006 Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields NeurIPS 2006 Learning to parse images of articulated bodies NeurIPS 2006 Learning to Rank with Nonsmooth Cost Functions NeurIPS 2006 Learning to Traverse Image Manifolds NeurIPS 2006 Learning with Hypergraphs: Clustering, Classification, and Embedding NeurIPS 2006 Linear Programming Relaxations and Belief Propagation -- An Empirical Study JMLR 2006 Linear State-Space Models for Blind Source Separation JMLR 2006 Logistic Regression for Single Trial EEG Classification NeurIPS 2006 Lower Bounds and Aggregation in Density Estimation JMLR 2006 Manifold Denoising NeurIPS 2006 Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples JMLR 2006