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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
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'15
'20
'25

Papers (including subtopics)

Learning Lightness From Human Judgement on Relative Reflectance CVPR 2015 Learning Local Invariant Mahalanobis Distances ICML 2015 Learning Multiple Visual Tasks While Discovering Their Structure CVPR 2015 Learning of Non-Parametric Control Policies with High-Dimensional State Features AISTATS 2015 Learning Overcomplete Latent Variable Models through Tensor Methods COLT 2015 Learning Parametric Distributions for Image Super-Resolution: Where Patch Matching Meets Sparse Coding ICCV 2015 Learning Parametric-Output HMMs with Two Aliased States ICML 2015 Learning Program Embeddings to Propagate Feedback on Student Code ICML 2015 Learning Query and Image Similarities With Ranking Canonical Correlation Analysis ICCV 2015 Learning Scale-Free Networks by Dynamic Node Specific Degree Prior ICML 2015 Learning Semantic Relationships for Better Action Retrieval in Images CVPR 2015 Learning Similarity Metrics for Dynamic Scene Segmentation CVPR 2015 Learning Sparse Low-Threshold Linear Classifiers JMLR 2015 Learning Spatially Regularized Correlation Filters for Visual Tracking ICCV 2015 Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels NeurIPS 2015 Learning structured densities via infinite dimensional exponential families NeurIPS 2015 Learning Structured Output Representation using Deep Conditional Generative Models NeurIPS 2015 Learning Submodular Losses with the Lovasz Hinge ICML 2015 Learning Temporal Embeddings for Complex Video Analysis ICCV 2015 Learning Theory of Randomized Kaczmarz Algorithm JMLR 2015 Learning to Boost Filamentary Structure Segmentation ICCV 2015 Learning to Detect Motion Boundaries CVPR 2015 Learning to Linearize Under Uncertainty NeurIPS 2015 Learning To Look Up: Realtime Monocular Gaze Correction Using Machine Learning CVPR 2015 Learning to Predict Saliency on Face Images ICCV 2015