Yang's research group wiki

calvin tasks: 1. run STWALK one more time in new graph

                        2. output graphs without filtering to jiashuo.
                        

jiasuho tasks: 1. visualization.

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• S. Chopra, R. Hadsell and Y. LeCun, Learning a similarity metric discriminatively, with application to face verification,“ 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), San Diego, CA, USA, 2005, pp. 539-546 vol.
• Presenter: Shi Lu

Abstract: Early version of contrastive loss and Smilarity metric

• Wu C Y , Manmatha R , Smola A J , et al. Sampling Matters in Deep Embedding Learning. 2017.
• Presenter: Yicong

Abstract: distance weighted sampling,different version of triplet loss

• David Qiu, Embedding and latent variable models using maximal correlation, 2016
• Presenter: Jiarong

• Monath, N., Zaheer, M., Silva, D., McCallum, A., & Ahmed, A. (2019, July). Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 714-722). ACM.
• Presenter: Runpeng

• Wang, L., Wu, J., Huang, S. L., Zheng, L., Xu, X., Zhang, L., & Huang, J. (2019, July). An efficient approach to informative feature extraction from multimodal data. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 5281-5288).
• Presenter: Calvin

• Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard Zemel. The Variational Fair Autoencoder.
• Presenter: Shi Lu

• Narayanaswamy, S., Paige, T. B., Van de Meent, J. W., Desmaison, A., Goodman, N., Kohli, P., … & Torr, P. (2017). Learning disentangled representations with semi-supervised deep generative models. In Advances in Neural Information Processing Systems (pp. 5925-5935).
• Presenter: Shi Lu

• Diederik P Kingma, Max Welling. Auto-Encoding Variational Bayes.
• Presenter: Yicong Li

• Yao Xu, Xueshuang Xiang, Meiyu Huang. Task-Driven Common Representation Learning via Bridge Neural Network, AAAI 2019
• Presenter: Mingyang Li

• Sun, Q., Liu, Y., Chua, T. S., & Schiele, B. (2019). Meta-transfer learning for few-shot learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 403-412).
• Presenter: Yang Tan

• Li, A., Luo, T., Lu, Z., Xiang, T., & Wang, L. (2019). Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 7212-7220).
• Presenter: Yicong Li

• Joshua Lee, Prasanna Sattigeri, Gregory Wornell, Learning New Tricks From Old Dogs: Multi-Source Transfer Learning From Pre-Trained Networks, NIPS 2019
• Presenter: Jingge Wang

• Pandhre, S., Mittal, H., Gupta, M., & Balasubramanian, V. N. (2018). STWalk: Learning trajectory representations in temporal graphs. ACM International Conference Proceeding Series, 210–219.
• Presenter: Calvin Chan

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