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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)

Infrared-Visible Cross-Modal Person Re-Identification with an X Modality AAAI 2020 Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition EMNLP 2020 Injecting Numerical Reasoning Skills into Language Models ACL 2020 iNLTK: Natural Language Toolkit for Indic Languages EMNLP 2020 In Neural Machine Translation, What Does Transfer Learning Transfer? ACL 2020 In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology ACL 2020 Insertion-Based Modeling for End-to-End Automatic Speech Recognition Interspeech 2020 INSET: Sentence Infilling with INter-SEntential Transformer ACL 2020 Instance-Adaptive Graph for EEG Emotion Recognition AAAI 2020 Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection CVPR 2020 Instance-Aware Image Colorization CVPR 2020 Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise AAAI 2020 Instance Selection for GANs NeurIPS 2020 Instance-wise Feature Grouping NeurIPS 2020 Integrating Deep Learning with Logic Fusion for Information Extraction AAAI 2020 Integrating Multimodal Information in Large Pretrained Transformers ACL 2020 Integrating Relation Constraints with Neural Relation Extractors AAAI 2020 Intelligent Analyses on Storytelling for Impact Measurement EMNLP 2020 Interactive Dual Generative Adversarial Networks for Image Captioning AAAI 2020 Interactive Multi-Label CNN Learning With Partial Labels CVPR 2020 Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? ACL 2020 Internet of Things (IoT) Discovery Using Deep Neural Networks WACV 2020 Interpretable Entity Representations through Large-Scale Typing EMNLP 2020 Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge ICML 2020 Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings ACL 2020