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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)

On Ranking in Survival Analysis: Bounds on the Concordance Index NeurIPS 2007 On Sparsity and Overcompleteness in Image Models NeurIPS 2007 On the Consistency of Multiclass Classification Methods JMLR 2007 On the Representer Theorem and Equivalent Degrees of Freedom of SVR JMLR 2007 Optimal ROC Curve for a Combination of Classifiers NeurIPS 2007 Parallelizing Support Vector Machines on Distributed Computers NeurIPS 2007 Penalized Model-Based Clustering with Application to Variable Selection JMLR 2007 People Tracking with the Laplacian Eigenmaps Latent Variable Model NeurIPS 2007 Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NeurIPS 2007 Predicting Partial Paths from Planning Problem Parameters RSS 2007 Predictive Matrix-Variate t Models NeurIPS 2007 Probabilistic Matrix Factorization NeurIPS 2007 Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes JMLR 2007 Random Features for Large-Scale Kernel Machines NeurIPS 2007 Random Projections for Manifold Learning NeurIPS 2007 Ranking the Best Instances JMLR 2007 Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing NeurIPS 2007 Receptive Fields without Spike-Triggering NeurIPS 2007 Refinable Kernels JMLR 2007 Regularized Boost for Semi-Supervised Learning NeurIPS 2007 Relational Dependency Networks JMLR 2007 Retrieved context and the discovery of semantic structure NeurIPS 2007 Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data JMLR 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Scene Segmentation with CRFs Learned from Partially Labeled Images NeurIPS 2007