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Learning Types

32,670 papers (1 classified directly here)

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)
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Papers (including subtopics)

Unsupervised Out-of-Domain Detection via Pre-trained Transformers ACL 2021 Unsupervised Paraphrasing with Pretrained Language Models EMNLP 2021 Unsupervised Part Segmentation Through Disentangling Appearance and Shape CVPR 2021 Unsupervised Pre-Training for Person Re-Identification CVPR 2021 Unsupervised Pronoun Resolution via Masked Noun-Phrase Prediction ACL 2021 Unsupervised Real-World Image Super Resolution via Domain-Distance Aware Training CVPR 2021 Unsupervised Relation Extraction: A Variational Autoencoder Approach EMNLP 2021 Unsupervised Representation Learning via Neural Activation Coding ICML 2021 UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering CVPR 2021 Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders AAAI 2021 Unsupervised Training of a DNN-Based Formant Tracker Interspeech 2021 Unsupervised Translation of German–Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language EMNLP 2021 Unsupervised Visual Representation Learning by Tracking Patches in Video CVPR 2021 UP-DETR: Unsupervised Pre-Training for Object Detection With Transformers CVPR 2021 UPFlow: Upsampling Pyramid for Unsupervised Optical Flow Learning CVPR 2021 Using Adversarial Attacks to Reveal the Statistical Bias in Machine Reading Comprehension Models ACL 2021 Using Hindsight to Anchor Past Knowledge in Continual Learning AAAI 2021 Using Optimal Transport as Alignment Objective for fine-tuning Multilingual Contextualized Embeddings EMNLP 2021 Using Pause Information for More Accurate Entity Recognition EMNLP 2021 Using Question Answering Rewards to Improve Abstractive Summarization EMNLP 2021 Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users AAAI 2021 Using Random Effects to Account for High-Cardinality Categorical Features and Repeated Measures in Deep Neural Networks NeurIPS 2021 Using Unsupervised Learning for Data-driven Procurement Demand Aggregation AAAI 2021 Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction EMNLP 2021 UXLA: A Robust Unsupervised Data Augmentation Framework for Zero-Resource Cross-Lingual NLP ACL 2021