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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)

Inference Offloading for Cost-Sensitive Binary Classification at the Edge AAAI 2026 Inference with non-differentiable surrogate loss in a general high-dimensional classification framework JMLR 2026 Information-Theoretic Minimal Sufficient Representation for Multi-Domain Knowledge Graph Completion AAAI 2026 Informative Subgraph Extraction with Deep Reinforcement Learning for Drug-Drug Interaction Prediction AAAI 2026 Integral-based Knockoffs Inference for Partially Linear Models AAAI 2026 Integrating Fourier Neural Operators into High-Fidelity Helicopter Flight Simulation for Real-Time Urban Wind Prediction AAAI 2026 Integrating Multi-scale and Multi-filtration Topological Features for Medical Image Classification WACV 2026 Intention Knowledge Graph Construction for User Intention Relation Modeling EACL 2026 Interaction-via-Actions: Cattle Interaction Detection with Joint Learning of Action-Interaction Latent Space WACV 2026 Interest-driven Deep Multi-modal Clustering AAAI 2026 Interest-Shift-Aware Logical Reasoning for Efficient Long-Sequence Recommendation AAAI 2026 Interpretable Graph-Language Modeling for Detecting Youth Illicit Drug Use EACL 2026 Interpretable Machine Learning for In-Home Mild Cognitive Impairment Detection AAAI 2026 Intervention-Aware Time Series Modeling: Capturing and Evaluating Feature Dependencies AAAI 2026 Intra-Class Unbiased Prototype Aggregation and Classifier Collaboration for Personalized Federated Learning AAAI 2026 Intraoperative 2D/3D Registration via Spherical Similarity Learning and Differentiable Levenberg-Marquardt Optimization WACV 2026 Invariant Feature Learning for Counterfactual Watch-time Prediction in Video Recommendation AAAI 2026 Invariant Representation Learning for Memory Behavior Modeling via Adaptive Environment Separation AAAI 2026 Investigating Data Pruning for Pretraining Biological Foundation Models at Scale AAAI 2026 IQGS: Instance Query-based Gaussian Segmentation AAAI 2026 ISALux: Illumination and Semantics-Aware Transformer Employing Mixture of Experts for Low Light Image Enhancement WACV 2026 Is Sentiment Banana-Shaped? Exploring the Geometry and Portability of Sentiment Concept Vectors EACL 2026 Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning AAAI 2026 ITPP: Learning Disentangled Event Dynamics in Marked Temporal Point Processes AAAI 2026 ITSELF: Attention Guided Fine-Grained Alignment for Vision-Language Retrieval WACV 2026