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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

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2000
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Papers (including subtopics)

Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology CVPR 2024 Feature Unlearning for Pre-trained GANs and VAEs AAAI 2024 FeatWalk: Enhancing Few-Shot Classification through Local View Leveraging AAAI 2024 FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise AAAI 2024 FedCD: Federated Semi-Supervised Learning with Class Awareness Balance via Dual Teachers AAAI 2024 FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning AAAI 2024 FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels AAAI 2024 Federated Adaptation for Foundation Model-based Recommendations IJCAI 2024 Federated Causal Discovery from Heterogeneous Data ICLR 2024 Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users AAAI 2024 Federated Continual Learning via Prompt-based Dual Knowledge Transfer ICML 2024 Federated Ensemble-Directed Offline Reinforcement Learning NeurIPS 2024 Federated Generalized Category Discovery CVPR 2024 Federated Graph Learning for Cross-Domain Recommendation NeurIPS 2024 Federated Graph Learning under Domain Shift with Generalizable Prototypes AAAI 2024 Federated Label-Noise Learning with Local Diversity Product Regularization AAAI 2024 Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method NeurIPS 2024 Federated Learning over Connected Modes NeurIPS 2024 Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024 Federated Linear Contextual Bandits with Heterogeneous Clients AISTATS 2024 Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation AAAI 2024 Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning ICLR 2024 Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization AAAI 2024 FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning AAAI 2024 FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024