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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)

Confidence Weighted Mean Reversion Strategy for On-Line Portfolio Selection AISTATS 2011 Continuous-Time Regression Models for Longitudinal Networks NeurIPS 2011 Convergence of Distributed Asynchronous Learning Vector Quantization Algorithms JMLR 2011 Convergent Bounds on the Euclidean Distance NeurIPS 2011 Convergent Fitted Value Iteration with Linear Function Approximation NeurIPS 2011 Convex and Network Flow Optimization for Structured Sparsity JMLR 2011 Co-regularized Multi-view Spectral Clustering NeurIPS 2011 Cross-Domain Object Matching with Model Selection AISTATS 2011 Crowdclustering NeurIPS 2011 Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Functions on Graphs JMLR 2011 Data Skeletonization via Reeb Graphs NeurIPS 2011 Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011 Deep Learning for Efficient Discriminative Parsing AISTATS 2011 Deep Sparse Rectifier Neural Networks AISTATS 2011 Demixed Principal Component Analysis NeurIPS 2011 Dimensionality Reduction for Spectral Clustering AISTATS 2011 Dimensionality Reduction Using the Sparse Linear Model NeurIPS 2011 Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators NeurIPS 2011 Dirichlet Process Mixtures of Generalized Linear Models JMLR 2011 Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood JMLR 2011 Discussion of “Learning Scale Free Networks by Reweighted ℓ_1 regularization” AISTATS 2011 Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” AISTATS 2011 Discussion of “The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling” AISTATS 2011 Discussion of “The Neural Autoregressive Distribution Estimator” AISTATS 2011 Distance Dependent Chinese Restaurant Processes JMLR 2011