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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)

K-SRL: Instance-based Learning for Semantic Role Labeling COLING 2016 k-variates++: more pluses in the k-means++ ICML 2016 L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs JMLR 2016 L1-regularized Neural Networks are Improperly Learnable in Polynomial Time ICML 2016 Labeled Data Generation with Encoder-Decoder LSTM for Semantic Slot Filling Interspeech 2016 Label Embedding for Zero-shot Fine-grained Named Entity Typing COLING 2016 Language classification from bilingual word embedding graphs COLING 2016 Language Identification Based on Generative Modeling of Posteriorgram Sequences Extracted from Frame-by-Frame DNNs and LSTM-RNNs Interspeech 2016 Language Recognition via Sparse Coding Interspeech 2016 Laplacian Patch-Based Image Synthesis CVPR 2016 Large Margin Discriminant Dimensionality Reduction in Prediction Space NeurIPS 2016 Large-Margin Softmax Loss for Convolutional Neural Networks ICML 2016 Large Scale Online Kernel Learning JMLR 2016 Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016 Latent Embeddings for Zero-Shot Classification CVPR 2016 Latent Space Inference of Internet-Scale Networks JMLR 2016 Latent Topic Embedding COLING 2016 Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP) CVPR 2016 Launch and Iterate: Reducing Prediction Churn NeurIPS 2016 Learnable Visual Markers NeurIPS 2016 Learned Region Sparsity and Diversity Also Predicts Visual Attention NeurIPS 2016 Learning Activity Progression in LSTMs for Activity Detection and Early Detection CVPR 2016 Learning Acyclic Directed Mixed Graphs from Observations and Interventions PGM 2016 Learning a Discriminative Null Space for Person Re-Identification CVPR 2016 Learning Aligned Cross-Modal Representations From Weakly Aligned Data CVPR 2016