Learning Types
56,253 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Self-Supervised Learning (8,965)
Adversarial Learning (5,204)
Unsupervised Learning (4,874)
Transfer Learning (4,808)
Weakly Supervised Learning (3,938)
Contrastive Learning (3,748)
Zero-Shot Learning (3,130)
Semi-Supervised Learning (3,128)
Reinforcement Learning (3,118)
Multi-Task Learning (2,556)
Evaluation (2,164)
Continual Learning (2,107)
Active Learning (1,983)
Few-Shot Learning (1,840)
Deep Learning (1,404)
Online Learning (1,360)
Multi-Armed Bandits (1,327)
Multimodal Learning (1,289)
Supervised Learning (986)
Multi-Agent Systems (813)
Uncertainty Quantification (805)
Causal Inference (636)
Robustness (576)
Retrieval-Augmented Generation (565)
Fine-Tuning (490)
Ensemble Learning (482)
In-Context Learning (439)
Multi-Label Classification (430)
Imitation Learning (387)
Prompt Engineering (270)
Multi-Lingual Learning (269)
Distribution Shift (264)
Reinforcement Learning from Human Feedback (209)
Regularization (207)
Exploration-Exploitation (203)
Generative Models (200)
Multi-Objective Optimization (185)
Out-of-Distribution Detection (176)
Sparse Learning (165)
Sampling (150)
Preference Learning (136)
Offline Reinforcement Learning (130)
Multi-Label Learning (128)
Markov Decision Process (127)
Neural Architecture Search (122)
Multi-Instance Learning (121)
Multi-View Learning (117)
Robust Learning (110)
Generative Model (110)
Time Series (108)
Large Language Models (104)
Exploration (103)
Hyperparameter Optimization (99)
Machine Unlearning (95)
Imbalanced Learning (93)
Machine Translation (93)
Multi-Class Classification (85)
Differential Privacy (82)
Time Series Analysis (71)
Reasoning (70)
Calibration (67)
Structure Learning (66)
Physics-Informed Learning (62)
Class Imbalance (58)
Model-Based RL (55)
Interactive Learning (55)
Multi-Domain Learning (47)
Inverse Reinforcement Learning (46)
Crowdsourcing (40)
Off-Policy Learning (38)
Label Noise (38)
Noisy Label Learning (35)
Offline RL (32)
Attention (32)
Evolutionary Algorithm (32)
Decision Making (31)
Policy Learning (30)
Personalization (28)
Low-Resource Learning (26)
Collaborative Filtering (25)
Self-Training (24)
Sequential Modeling (24)
Parameter Estimation (23)
Survival Analysis (21)
Machine Learning (20)
Parameter-Efficient Fine-Tuning (20)
Synthetic Data Generation (20)
Annotation (18)
Symbolic Regression (18)
AutoML (16)
Security (15)
Multi-Source Learning (13)
Distant Supervision (13)
Text Generation (11)
Distributional Reinforcement Learning (9)
Sentiment Analysis (9)
Multi-Hop Reasoning (9)
Language Modeling (9)
Code Generation (8)
Multi-Object Tracking (8)
Natural Language Inference (7)
Chain-of-Thought (6)
Question Answering (5)
Papers per year
1
8
12
26
18
20
135
136
147
149
220
231
316
526
460
477
660
1,314
2,083
3,689
4,652
5,914
6,826
8,201
8,755
9,258
2,019
2000
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Papers (including subtopics)
MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
CVPR 2020
Masking Orchestration: Multi-Task Pretraining for Multi-Role Dialogue Representation Learning
AAAI 2020
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters
Interspeech 2020
MAST: A Memory-Augmented Self-Supervised Tracker
CVPR 2020
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
AAAI 2020
MAST: Multimodal Abstractive Summarization with Trimodal Hierarchical Attention
EMNLP 2020
Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality
COLING 2020
MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization
ACL 2020
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
AAAI 2020
Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness
NeurIPS 2020
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning
ICML 2020
Maximum Margin Multi-Dimensional Classification
AAAI 2020
Maximum Nash Welfare and Other Stories About EFX
IJCAI 2020
Maxmin Q-learning: Controlling the Estimation Bias of Q-learning
ICLR 2020
May I Ask Who’s Calling? Named Entity Recognition on Call Center Transcripts for Privacy Law Compliance
EMNLP 2020
McFlow: Monte Carlo Flow Models for Data Imputation
CVPR 2020
Measurement Dependence Inducing Latent Causal Models
UAI 2020
Measuring and Improving the Use of Graph Information in Graph Neural Networks
ICLR 2020
Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View
AAAI 2020
Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
ICLR 2020
Measuring Emotions in the COVID-19 Real World Worry Dataset
ACL 2020
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications
IJCAI 2020
Median Matrix Completion: from Embarrassment to Optimality
ICML 2020
MeDIL: A Python Package for Causal Modelling
PGM 2020
Meeting the 2020 Duolingo Challenge on a Shoestring
ACL 2020