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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)

TopNet: Structural Point Cloud Decoder CVPR 2019 Topology Optimization based Graph Convolutional Network IJCAI 2019 To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks ACL 2019 Toward Realistic Image Compositing With Adversarial Learning CVPR 2019 Towards Accurate One-Stage Object Detection With AP-Loss CVPR 2019 Towards Architecture-Agnostic Neural Transfer: a Knowledge-Enhanced Approach IJCAI 2019 Towards Automated Semantic Role Labelling of Hindi-English Code-Mixed Tweets EMNLP 2019 Towards Better Accuracy and Robustness with Localized Adversarial Training AAAI 2019 Towards Better Interpretability in Deep Q-Networks AAAI 2019 Towards Comprehensive Description Generation from Factual Attribute-value Tables ACL 2019 Towards Debiasing Fact Verification Models EMNLP 2019 Towards Fine-grained Text Sentiment Transfer ACL 2019 Towards Fluid Machine Intelligence: Can We Make a Gifted AI? AAAI 2019 Towards Gene Function Prediction via Multi-Networks Representation Learning AAAI 2019 Towards High-Fidelity Nonlinear 3D Face Morphable Model CVPR 2019 Towards Incremental Learning of Word Embeddings Using Context Informativeness ACL 2019 Towards Language Agnostic Universal Representations ACL 2019 Towards Latent Attribute Discovery From Triplet Similarities ICCV 2019 Towards Linear Time Neural Machine Translation with Capsule Networks EMNLP 2019 Towards Lossless Encoding of Sentences ACL 2019 Towards Making a Dependency Parser See EMNLP 2019 Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper) ACL 2019 Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies AAAI 2019 Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale Layer AAAI 2019 Towards Optimal Structured CNN Pruning via Generative Adversarial Learning CVPR 2019