Reading group meets every Friday at 4:15pm.
How to Participate (Read this first!)
| Date | Presenter | Topic | Reading | Slides |
|---|---|---|---|---|
| Feb 21,2020 | Tan Yang | transfer learning | W. Zhang and D. Wu, “Discriminative Joint Probability Maximum Mean Discrepancy ( DJP-MMD ) for Domain Adaptation.” | slide |
| Week 2 | Li Mingyang | self-supervised learning | A Simple Framework for Contrastive Learning of Visual Representations | slide |
| Week 3 | Shen Ruhui | transfer learning | Massimiliano Patacchiola et al. Deep Kernel Transfer in Gaussian Process for Few-Shot Learning | slide |
| Week 4 | Fan Jiashuo | network embedding | Link Prediction Algorithms for Social Networks based on Machine Learning and HARP | slide |
| Week 5 | Yang Jingyun | medical image | retina_unet.pdf | slide |
| Week 6 | Wang Jingge | transfer learning | Universal Domain Adaptation | slide |
| Week 7 | Calvin | network embedding | Author2Vec: Learning Author Representations by Combining Content and Link Information | slide |
| Week 8 | Yicong Li | Transfer Learning | Transfer Learning by Adaptive Merging of Multiple Models | slide |
| Date | Presenter | Topic | Reading | Slides |
|---|---|---|---|---|
| Week9 | Yang Tan | transfer learning | geometric_dataset_distances_via_optimal_transport.pdf | slides |
| Week10 | Mingyang Li | representation learning | generative_cross_modal_retrieval.pdf | look_imagine_and_match-_improving_textual-visual_cross-modal_retrieval_with_generative_models.ppt |
| Week11 | Ruhui Shen | transfer learning | active_learning_framework_of_informative_p53_cancer_rescue_mutants.pdf | |
| Week12 | Jingyun Yang | |||
| Week13 | Jingge Wang | Transfer Learning | Deep cocktail network | slide |
| Week14 | Calvin | |||
| Week15 | Yicong Li | Noisy Labels | 1804.06872.pdf | slide |
| Week16 | Jiashuo Fan |
| Paper Name | Notes | Added by |
|---|---|---|
| R. Chen, T. Chen, X. Hui, H. Wu, G. Li, and L. Lin, “Knowledge Graph Transfer Network for Few-Shot Recognition,” 2019. | few-shot learning, transfer learning, knowledge graph | yang |
| B. Tan, Y. Song, E. Zhong, and Q. Yang, “Transitive Transfer Learning Categories and Subject Descriptors,” Kdd, pp. 1155–1164, 2015 | transitivity in transfer learning (1/2) | yang |
| B. Tan, Y. Zhang, S. J. Pan, and Q. Yang, “Distant domain transfer learning,” 31st AAAI Conf. Artif. Intell. AAAI 2017, pp. 2604–2610, 2017 | transitivity in transfer learning (2/2) | yang |
| I. Redko, E. Morvant, A. Habrard, M. Sebban, and Y. Bennani, Advances in Domain Adaptation Theory. Elsevier Science, 2019. (Textbook) | domain adaptation, theory (can use multiple meetings) | yang |
| B. B. Damodaran, B. Kellenberger, R. D. Tuia, and N. Courty, “DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 11208 LNCS, pp. 467–483, 2018. | transfer learning, domain adaptation | yang |
| Y. Song et al., “Improving Unsupervised Domain Adaptation with Variational Information Bottleneck,” 2019. | domain adaptation, information theory, | yang |