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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
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'25

Papers (including subtopics)

The Feature Selection Path in Kernel Methods AISTATS 2010 The Group Dantzig Selector AISTATS 2010 The LASSO risk: asymptotic results and real world examples NeurIPS 2010 The Maximal Causes of Natural Scenes are Edge Filters NeurIPS 2010 The Multidimensional Wisdom of Crowds NeurIPS 2010 The SHOGUN Machine Learning Toolbox JMLR 2010 Tight Sample Complexity of Large-Margin Learning NeurIPS 2010 Tiled convolutional neural networks NeurIPS 2010 t-logistic regression NeurIPS 2010 Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models NeurIPS 2010 Towards Property-Based Classification of Clustering Paradigms NeurIPS 2010 Towards Understanding Situated Natural Language AISTATS 2010 Trading off Mistakes and Don't-Know Predictions NeurIPS 2010 Training and Testing Low-degree Polynomial Data Mappings via Linear SVM JMLR 2010 Transduction with Matrix Completion: Three Birds with One Stone NeurIPS 2010 Tree Decomposition for Large-Scale SVM Problems JMLR 2010 Tree-Structured Stick Breaking for Hierarchical Data NeurIPS 2010 Two-Layer Generalization Analysis for Ranking Using Rademacher Average NeurIPS 2010 Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach AISTATS 2010 Understanding the difficulty of training deep feedforward neural networks AISTATS 2010 Universal Consistency of Multi-Class Support Vector Classification NeurIPS 2010 Universal Kernels on Non-Standard Input Spaces NeurIPS 2010 Unsupervised Aggregation for Classification Problems with Large Numbers of Categories AISTATS 2010 Unsupervised Kernel Dimension Reduction NeurIPS 2010 Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels JMLR 2010