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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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Papers (including subtopics)

Matrix Completion from Power-Law Distributed Samples NeurIPS 2009 Maximin affinity learning of image segmentation NeurIPS 2009 Maximum Entropy Discrimination Markov Networks JMLR 2009 Maximum likelihood trajectories for continuous-time Markov chains NeurIPS 2009 Measuring Invariances in Deep Networks NeurIPS 2009 Measuring model complexity with the prior predictive NeurIPS 2009 Modeling Social Annotation Data with Content Relevance using a Topic Model NeurIPS 2009 Modeling the spacing effect in sequential category learning NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Model Monitor (M2): Evaluating, Comparing, and Monitoring Models JMLR 2009 Multi-Label Prediction via Compressed Sensing NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Multiple Incremental Decremental Learning of Support Vector Machines NeurIPS 2009 Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions JMLR 2009 NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM JMLR 2009 Nieme: Large-Scale Energy-Based Models JMLR 2009 No evidence for active sparsification in the visual cortex NeurIPS 2009 Noisy Generalized Binary Search NeurIPS 2009 Nonextensive Information Theoretic Kernels on Measures JMLR 2009 Nonlinear directed acyclic structure learning with weakly additive noise models NeurIPS 2009 Nonlinear Learning using Local Coordinate Coding NeurIPS 2009 Nonlinear Models Using Dirichlet Process Mixtures JMLR 2009 Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations NeurIPS 2009 Nonparametric Greedy Algorithms for the Sparse Learning Problem NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009