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This shows you the differences between two versions of the page.

--- reading_group [2017/05/25 00:23] – yang
+++ reading_group [2017/08/31 22:28] (current) – yang
@@ Line 1: / Line 1: @@
-=====Transfer learning reading group=====
+[[trans_learn:repository | Access code repository]]
-A reading group to discuss recent or classical papers on transfer learning methodology and other interesting theory topics.
-**Time:  Monday 4-5pm**
-**// :!: 端午节 Schedule change (week 5/29-6/2): Wednesday 4:30-5:30pm//**
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+[[trans_learn:reading_group | Reading group page]]
-====Schedule====
-===5/15/2017===
-  * Presenter: Yajie
-  * Paper 1 (main): Feng Liu, Guanquan Zhang, Haiyan Lu, Jie Lu,  {{ :alternating_diffusion_map.pdf | Heterogeneous Unsupervised Cross-domain Transfer Learning.}}
-  * Paper 2: Ye, Ke, and Lekheng Lim. {{ ::grassmannan_distance_shubert_variaty.pdf | Schubert varieties and distances between subspaces of different dimensions.}} SIAM Journal on Matrix Analysis and Applications 37.3 (2014): 1176-1197.
-===5/22/2017===
-  * Presenter: Yang
-  * Paper 1 (main):  R.R. Lederman, R Talmon, {{ :alternating_diffusion_map.pdf | Learning the geometry of common latent variables using alternating-diffusion }}, Appl. Comput. Harmon. Anal. (2015)
-  * Paper 2: O. Katz, R. Talmon, Y.-L. Lo, H.-T. Wu, {{ :data-fusion-by-multi-sensor-diffusion-map.pdf
-| Diffusion-based nonlinear filtering for multimodal data fusion with application to sleep stage assessment}}
-===5/29/2017===
-  * Presenter: Yajie
-  * Paper 1 (main): Nguyen, Hien V., et al, {{ :dash-n_joint_hierarchical_domain_adaptation_and_feature_learning.pdf | DASH-N: Joint hierarchical domain adaptation and feature learning }}, IEEE Transactions on Image Processing 24.12 (2015): 5479-5491.
-  * Paper 2: Lin, Liang, et al， {{ :cross-domain_visual_matching_via_generalized_similarity_measure_and_feature_learning.pdf | Cross-domain visual matching via generalized similarity measure and feature learning }}, IEEE transactions on pattern analysis and machine intelligence (2016).
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-====Paper suggestions====
-* Add a paper that you want us to discuss in the future
-====Useful resources====
- ...