- Data: 16.12.2019 (Monday) Speaker : Hui-Po Paper: The introduction of domain adaptation
- Data: 06.01.2020 (Monday) Speaker: Paper:
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- Deep domain confusion: Maximizing for domain invariance [pdf] [slides]
- Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, Trevor Darrell
- ArXiv, 2014
- Presented by Hui-Po on 20191205
- Domain-Adversarial Training of Neural Networks [pdf] [slides]
- Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor Lempitsky
- JMLR, 2016
- Presented by Hui-Po on 20191205
- Adversarial Discriminative Domain Adaptation [pdf] [slides]
- Eric Tzeng, Judy Hoffman, Kate Saenko, Trevor Darrell
- CVPR, 2017
- Presented by Hui-Po on 20191205
- A dirt-t approach to unsupervised domain adaptation [pdf] [slides]
- Rui Shu, Hung H. Bui, Hirokazu Narui, Stefano Ermon
- ICLR, 2018
- Presented by Hui-Po on 20191205
- CyCADA: Cycle-Consistent Adversarial Domain Adaptation [pdf] [slides]
- Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell
- ICML, 2018, and JMLR, 2019
- Presented by Hui-Po on 20191205
- Large-scale long-tailed recognition in an open world [pdf] [slides]
- Ziwei Liu, Zhongqi Miao, Xiaohang Zhan, Jiayun Wang, Boqing Gong, and Stella X Yu.
- In CVPR, 2019
- Class-balanced loss based on effective number of samples [pdf] [slides]
- Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, and Serge Belongie
- In CVPR, 2019
- Prototypical networks for few-shot learning [pdf] [slides]
- Jake Snell, Kevin Swersky, and Richard Zemel
- In NeurIPS, 2017
- Learning from imbalanced data [pdf] [slides]
- Haibo He and Edwardo A Garcia
- TKDE, 2009