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)
On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions
EACL 2021
On the Effect of Auxiliary Tasks on Representation Dynamics
AISTATS 2021
On the Embeddings of Variables in Recurrent Neural Networks for Source Code
NAACL 2021
On the Equivalence between Neural Network and Support Vector Machine
NeurIPS 2021
On the Estimation of Network Complexity: Dimension of Graphons
JMLR 2021
On the evolution of syntactic information encoded by BERT’s contextualized representations
EACL 2021
On the Faster Alternating Least-Squares for CCA
AISTATS 2021
On-the-fly Rectification for Robust Large-Vocabulary Topic Inference
ICML 2021
On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models
ICML 2021
On the Generation of Medical Dialogs for COVID-19
ACL 2021
On the Generative Utility of Cyclic Conditionals
NeurIPS 2021
On the geometry of generalization and memorization in deep neural networks
ICLR 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
NeurIPS 2021
On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies
NAACL 2021
On the interplay between data structure and loss function in classification problems
NeurIPS 2021
On the mapping between Hopfield networks and Restricted Boltzmann Machines
ICLR 2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling
NeurIPS 2021
On the Power of Edge Independent Graph Models
NeurIPS 2021
On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise
ICML 2021
On the price of explainability for some clustering problems
ICML 2021
On the Problem of Underranking in Group-Fair Ranking
ICML 2021
On the proliferation of support vectors in high dimensions
AISTATS 2021
On the Random Conjugate Kernel and Neural Tangent Kernel
ICML 2021
On the Role of Optimization in Double Descent: A Least Squares Study
NeurIPS 2021
On the Sample Complexity of Learning under Geometric Stability
NeurIPS 2021