conftrace_

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

21

30

55

40

51

225

219

249

257

357

364

480

942

818

966

1,394

2,092

3,114

4,415

4,853

5,064

5,371

5,992

6,412

5,823

1,475

2000

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Papers (including subtopics)

Gaussian process regression with Student-t likelihood NeurIPS 2009 Generalization Bounds for Ranking Algorithms via Algorithmic Stability JMLR 2009 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NeurIPS 2009 Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models NeurIPS 2009 Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NeurIPS 2009 Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction NeurIPS 2009 Group Sparse Coding NeurIPS 2009 Hash Kernels for Structured Data JMLR 2009 Heavy-Tailed Symmetric Stochastic Neighbor Embedding NeurIPS 2009 Heterogeneous multitask learning with joint sparsity constraints NeurIPS 2009 Hierarchical Learning of Dimensional Biases in Human Categorization NeurIPS 2009 Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions NeurIPS 2009 Hierarchical Modeling of Local Image Features through L_p-Nested Symmetric Distributions NeurIPS 2009 Incorporating Functional Knowledge in Neural Networks JMLR 2009 Indian Buffet Processes with Power-law Behavior NeurIPS 2009 Individuation, Identification and Object Discovery NeurIPS 2009 Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NeurIPS 2009 Java-ML: A Machine Learning Library JMLR 2009 Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions NeurIPS 2009 Kernel Methods for Deep Learning NeurIPS 2009 Kernels and learning curves for Gaussian process regression on random graphs NeurIPS 2009 Label Selection on Graphs NeurIPS 2009 Lattice Regression NeurIPS 2009 Learning Approximate Sequential Patterns for Classification JMLR 2009 Learning a Small Mixture of Trees NeurIPS 2009