conftrace_

Learning Types

32,670 papers (1 classified directly here)

Subtopics · a paper can sit in several, so these overlap

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)

Papers per year

1

22

25

29

26

38

46

60

109

129

179

310

686

1,294

2,286

3,018

3,254

3,930

4,067

4,819

5,737

2,605

'10

'15

'20

'25

Papers (including subtopics)

Learning Convolutional Neural Networks for Graphs ICML 2016 Learning Deep Embeddings with Histogram Loss NeurIPS 2016 Learning Deep Feature Representations With Domain Guided Dropout for Person Re-Identification CVPR 2016 Learning Deep Features for Discriminative Localization CVPR 2016 Learning Deep Parsimonious Representations NeurIPS 2016 Learning Deep Representation for Imbalanced Classification CVPR 2016 Learning Deep Structure-Preserving Image-Text Embeddings CVPR 2016 Learning Dense Correspondence via 3D-Guided Cycle Consistency CVPR 2016 Learning feed-forward one-shot learners NeurIPS 2016 Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs NeurIPS 2016 Learning From the Mistakes of Others: Matching Errors in Cross-Dataset Learning CVPR 2016 Learning Granger Causality for Hawkes Processes ICML 2016 Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions CVPR 2016 Learning Multiagent Communication with Backpropagation NeurIPS 2016 Learning Neural Network Representations Using Cross-Lingual Bottleneck Features with Word-Pair Information Interspeech 2016 Learning Relaxed Deep Supervision for Better Edge Detection CVPR 2016 Learning Simple Algorithms from Examples ICML 2016 Learning Structured Inference Neural Networks With Label Relations CVPR 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NeurIPS 2016 Learning to Match Aerial Images With Deep Attentive Architectures CVPR 2016 Learning Transferrable Representations for Unsupervised Domain Adaptation NeurIPS 2016 Learning What and Where to Draw NeurIPS 2016 Local Similarity-Aware Deep Feature Embedding NeurIPS 2016 LOMo: Latent Ordinal Model for Facial Analysis in Videos CVPR 2016 Matching Networks for One Shot Learning NeurIPS 2016