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 Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems
COLT 2020
On the Detection of Digital Face Manipulation
CVPR 2020
On the diminishing return of labeling clinical reports
EMNLP 2020
On the Discrepancy between Density Estimation and Sequence Generation
EMNLP 2020
On the Equivalence between Positional Node Embeddings and Structural Graph Representations
ICLR 2020
On the Error Resistance of Hinge-Loss Minimization
NeurIPS 2020
On the Expressive Power of Kernel Methods and the Efficiency of Kernel Learning by Association Schemes
ALT 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods
ICML 2020
On the Helpfulness of Document Context to Sentence Simplification
COLING 2020
On the Hierarchical Information in a Single Contextualised Word Representation (Student Abstract)
AAAI 2020
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks
EMNLP 2020
On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification
IJCAI 2020
On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers
EMNLP 2020
On the Iteration Complexity of Hypergradient Computation
ICML 2020
On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks
AAAI 2020
On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels
COLT 2020
On the optimality of kernels for high-dimensional clustering
AISTATS 2020
On the Optimal Weighted ℓ_2 Regularization in Overparameterized Linear Regression
NeurIPS 2020
On the Parameterized Complexity of Clustering Incomplete Data into Subspaces of Small Rank
AAAI 2020
On the Power of Compressed Sensing with Generative Models
ICML 2020
On the Power of Louvain in the Stochastic Block Model
NeurIPS 2020
On the Practical Ability of Recurrent Neural Networks to Recognize Hierarchical Languages
COLING 2020
On the Relationship Between Probabilistic Circuits and Determinantal Point Processes
UAI 2020
On the Robustness of Language Encoders against Grammatical Errors
ACL 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
NeurIPS 2020