Application Areas
34,437 papers (4 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Domain Adaptation (9,897)
Efficient Computing (8,226)
Data Augmentation (3,648)
Fairness (3,574)
Knowledge Distillation (3,219)
Privacy (3,022)
Domain Generalization (1,972)
Model Compression (1,736)
Risk Management (1,119)
Model Merging (592)
Recommender Systems (343)
Information Retrieval (249)
Text Classification (144)
Text Processing (2)
Papers per year
1
3
5
5
4
19
24
28
26
35
42
55
142
116
147
330
517
1,020
1,828
2,498
3,411
3,854
5,063
6,422
7,176
1,666
2000
'5
'10
'15
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'25
Papers (including subtopics)
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation
NeurIPS 2020
Trade the System Efficiency for the Income Equality of Drivers in Rideshare
IJCAI 2020
Trading Personalization for Accuracy: Data Debugging in Collaborative Filtering
NeurIPS 2020
Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers
ICML 2020
Training Binary Neural Networks using the Bayesian Learning Rule
ICML 2020
Training Decision Trees as Replacement for Convolution Layers
AAAI 2020
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize
CVPR 2020
Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators
ICLR 2020
Training Generative Adversarial Networks with Limited Data
NeurIPS 2020
Training individually fair ML models with sensitive subspace robustness
ICLR 2020
Training Keyword Spotting Models on Non-IID Data with Federated Learning
Interspeech 2020
Training Noise-Robust Deep Neural Networks via Meta-Learning
CVPR 2020
Training Quantized Neural Networks With a Full-Precision Auxiliary Module
CVPR 2020
Training-Time-Friendly Network for Real-Time Object Detection
AAAI 2020
Training with Noise Adversarial Network: A Generalization Method for Object Detection on Sonar Image
WACV 2020
Train No Evil: Selective Masking for Task-Guided Pre-Training
EMNLP 2020
Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning
NeurIPS 2020
Transferable Calibration with Lower Bias and Variance in Domain Adaptation
NeurIPS 2020
Transferable Graph Optimizers for ML Compilers
NeurIPS 2020
Transfer Learning From Synthetic to Real-Noise Denoising With Adaptive Instance Normalization
CVPR 2020
Transfer Learning from Well-Curated to Less-Resourced Populations with HIV
MLHC 2020
Transfer Learning via ℓ_1 Regularization
NeurIPS 2020
Transferring and Regularizing Prediction for Semantic Segmentation
CVPR 2020
Transferring Cross-Domain Knowledge for Video Sign Language Recognition
CVPR 2020
Transformer Based Multi-Source Domain Adaptation
EMNLP 2020