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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
'5
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'25

Papers (including subtopics)

On the Identifiability and Estimation of Causal Location-Scale Noise Models ICML 2023 On the Identifiability and Interpretability of Gaussian Process Models NeurIPS 2023 On the Identifiability of Sparse ICA without Assuming Non-Gaussianity NeurIPS 2023 On the Implicit Bias of Linear Equivariant Steerable Networks NeurIPS 2023 On the Implicit Geometry of Cross-Entropy Parameterizations for Label-Imbalanced Data AISTATS 2023 On the Importance of Exploration for Generalization in Reinforcement Learning NeurIPS 2023 On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning ICML 2023 On the Importance of Feature Separability in Predicting Out-Of-Distribution Error NeurIPS 2023 On The Inadequacy of Optimizing Alignment and Uniformity in Contrastive Learning of Sentence Representations ICLR 2023 On the informativeness of supervision signals UAI 2023 On the Initialization of Graph Neural Networks ICML 2023 On the Interplay Between Misspecification and Sub-optimality Gap in Linear Contextual Bandits ICML 2023 On the Interpretability and Significance of Bias Metrics in Texts: a PMI-based Approach ACL 2023 On the Learnability of Multilabel Ranking NeurIPS 2023 On the Limitations of the Elo, Real-World Games are Transitive, not Additive AISTATS 2023 On the Optimality of Misspecified Kernel Ridge Regression ICML 2023 On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure JMLR 2023 On the Pitfall of Mixup for Uncertainty Calibration CVPR 2023 On the Power of SVD in the Stochastic Block Model NeurIPS 2023 On The Relative Error of Random Fourier Features for Preserving Kernel Distance ICLR 2023 On the Robustness of Normalizing Flows for Inverse Problems in Imaging ICCV 2023 On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion ICCV 2023 On the Robustness of Randomized Ensembles to Adversarial Perturbations ICML 2023 On the Robustness of Removal-Based Feature Attributions NeurIPS 2023 On the Role of Attention in Prompt-tuning ICML 2023