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

'5

'10

'15

'20

'25

Papers (including subtopics)

Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006 Image Retrieval and Classification Using Local Distance Functions NeurIPS 2006 implicit Online Learning with Kernels NeurIPS 2006 Incremental Algorithms for Hierarchical Classification JMLR 2006 Incremental Support Vector Learning: Analysis, Implementation and Applications JMLR 2006 Inducing Metric Violations in Human Similarity Judgements NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Infinite-Ï Limits For Tikhonov Regularization JMLR 2006 Information Bottleneck for Non Co-Occurrence Data NeurIPS 2006 Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons NeurIPS 2006 In-Network PCA and Anomaly Detection NeurIPS 2006 In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006 Isotonic Conditional Random Fields and Local Sentiment Flow NeurIPS 2006 Kernel-Based Learning of Hierarchical Multilabel Classification Models JMLR 2006 Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm NeurIPS 2006 Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting JMLR 2006 Kernels on Structured Objects Through Nested Histograms NeurIPS 2006 Large Margin Component Analysis NeurIPS 2006 Large Margin Hidden Markov Models for Automatic Speech Recognition NeurIPS 2006 Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis NeurIPS 2006 Large Scale Hidden Semi-Markov SVMs NeurIPS 2006 Large Scale Multiple Kernel Learning JMLR 2006 Large-Scale Sparsified Manifold Regularization NeurIPS 2006 Large Scale Transductive SVMs JMLR 2006 Learning annotated hierarchies from relational data NeurIPS 2006