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Domain Adaptation

183 directly classified papers

Papers per year

Papers

Unsupervised Model Personalization While Preserving Privacy and Scalability: An Open Problem CVPR 2020
Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment AAAI 2020
MetaMT, a Meta Learning Method Leveraging Multiple Domain Data for Low Resource Machine Translation AAAI 2020
iFAN: Image-Instance Full Alignment Networks for Adaptive Object Detection AAAI 2020
The TechQA Dataset ACL 2020
Geometry-aware domain adaptation for unsupervised alignment of word embeddings ACL 2020
KinGDOM: Knowledge-Guided DOMain Adaptation for Sentiment Analysis ACL 2020
Domain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes ACL 2020
Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation ACL 2020
Zero-Resource Cross-Domain Named Entity Recognition ACL 2020
Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization CVPR 2020
Transferring Cross-Domain Knowledge for Video Sign Language Recognition CVPR 2020
Open Compound Domain Adaptation CVPR 2020
RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real CVPR 2020
Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation CVPR 2020
Learning From Synthetic Animals CVPR 2020
Margin-aware Unsupervised Domain Adaptation for Cross-lingual Text Labeling EMNLP 2020
On Cross-Dataset Generalization in Automatic Detection of Online Abuse EMNLP 2020
The ADAPT’s Submissions to the WMT20 Biomedical Translation Task EMNLP 2020
Your Classifier can Secretly Suffice Multi-Source Domain Adaptation NIPS 2020
Domain Adaptation as a Problem of Inference on Graphical Models NIPS 2020
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NIPS 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift NIPS 2020
Universal Domain Adaptation through Self Supervision NIPS 2020
Domain Adaptation with BERT-based Domain Classification and Data Selection EMNLP 2019