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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'20
'25
Papers (including subtopics)
Optimal Classification under Performative Distribution Shift
NeurIPS 2024
Optimal Clustering with Bandit Feedback
JMLR 2024
Optimal Decision Tree and Adaptive Submodular Ranking with Noisy Outcomes
JMLR 2024
Optimal Design for Human Preference Elicitation
NeurIPS 2024
Optimal Exploration is no harder than Thompson Sampling
AISTATS 2024
Optimal Mechanism in a Dynamic Stochastic Knapsack Environment
AAAI 2024
Optimal Multiclass U-Calibration Error and Beyond
NeurIPS 2024
Optimal Sample Complexity of Contrastive Learning
ICLR 2024
Optimal Scalarizations for Sublinear Hypervolume Regret
NeurIPS 2024
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis
NeurIPS 2024
Optimal transport based adversarial patch to leverage large scale attack transferability
ICLR 2024
Optimal Weighted Random Forests
JMLR 2024
Optimal Zero-Shot Detector for Multi-Armed Attacks
AISTATS 2024
Optimising Distributions with Natural Gradient Surrogates
AISTATS 2024
Optimistic Information Directed Sampling
COLT 2024
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization
AAAI 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
JMLR 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property
AAAI 2024
Optimistic Rates for Learning from Label Proportions
COLT 2024
Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
UAI 2024
Optimistic Value Instructors for Cooperative Multi-Agent Reinforcement Learning
AAAI 2024
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
NeurIPS 2024
Optimization Framework for Semi-supervised Attributed Graph Coarsening
UAI 2024
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
NeurIPS 2024
Optimizing Automatic Differentiation with Deep Reinforcement Learning
NeurIPS 2024