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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)

Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis JMLR 2019 Local Relationship Learning With Person-Specific Shape Regularization for Facial Action Unit Detection CVPR 2019 Local to Global Learning: Gradually Adding Classes for Training Deep Neural Networks CVPR 2019 Location-Based End-to-End Speech Recognition with Multiple Language Models AAAI 2019 Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding AAAI 2019 Logistic Regression on Homomorphic Encrypted Data at Scale AAAI 2019 Long-Distance Dependencies Don’t Have to Be Long: Simplifying through Provably (Approximately) Optimal Permutations ACL 2019 Long Short-Term Memory with Dynamic Skip Connections AAAI 2019 Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks NAACL 2019 Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition AAAI 2019 Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-Grained Image Recognition CVPR 2019 Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation ICML 2019 Lorentzian Distance Learning for Hyperbolic Representations ICML 2019 Loss Landscapes of Regularized Linear Autoencoders ICML 2019 Lossless or Quantized Boosting with Integer Arithmetic ICML 2019 Lost in Interpretation: Predicting Untranslated Terminology in Simultaneous Interpretation NAACL 2019 Lovasz Convolutional Networks AISTATS 2019 Low-Bit Quantization for Attributed Network Representation Learning IJCAI 2019 Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees NeurIPS 2019 Low-Dimensional Density Ratio Estimation for Covariate Shift Correction AISTATS 2019 Low Permutation-rank Matrices: Structural Properties and Noisy Completion JMLR 2019 Low-Rank Tensor Completion With a New Tensor Nuclear Norm Induced by Invertible Linear Transforms CVPR 2019 Low Resource Automatic Intonation Classification Using Gated Recurrent Unit (GRU) Networks Pre-Trained with Synthesized Pitch Patterns Interspeech 2019 Low-Resource Name Tagging Learned with Weakly Labeled Data EMNLP 2019 Low-Resource Response Generation with Template Prior EMNLP 2019