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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
51
357
966
4,853
5,823
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Efficient Margin Maximizing with Boosting JMLR 2005 Fast Kernel Classifiers with Online and Active Learning JMLR 2005 Feature Selection for Unsupervised and Supervised Inference: The Emergence of Sparsity in a Weight-Based Approach JMLR 2005 Frames, Reproducing Kernels, Regularization and Learning JMLR 2005 Gaussian Processes for Ordinal Regression JMLR 2005 Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes JMLR 2005 Generalization Bounds for the Area Under the ROC Curve JMLR 2005 Information Bottleneck for Gaussian Variables JMLR 2005 Inner Product Spaces for Bayesian Networks JMLR 2005 Kernel Methods for Measuring Independence JMLR 2005 Large Margin Methods for Structured and Interdependent Output Variables JMLR 2005 Learning a Mahalanobis Metric from Equivalence Constraints JMLR 2005 Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005 Learning Module Networks JMLR 2005 Learning Multiple Tasks with Kernel Methods JMLR 2005 Learning the Kernel Function via Regularization JMLR 2005 Learning the Kernel with Hyperkernels JMLR 2005 Learning with Decision Lists of Data-Dependent Features JMLR 2005 Local Propagation in Conditional Gaussian Bayesian Networks JMLR 2005 Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application JMLR 2005 Managing Diversity in Regression Ensembles JMLR 2005 Maximum Margin Algorithms with Boolean Kernels JMLR 2005 Multiclass Boosting for Weak Classifiers JMLR 2005 Multiclass Classification with Multi-Prototype Support Vector Machines JMLR 2005 On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning JMLR 2005