Xiang Zhang, Ph.D. Student
Computer Science Department
Courant Institute of Mathematical Sciences
New York University
xiang.zhang [a t] nyu.edu
Room 1231, 715 Broadway, New York, NY 10003
I am a second year Ph.D. student under the advisement of professor Yann LeCun with an interest in machine learning, including deep learning,
numerical optimization, and some learning theory. Before being a Ph.D. student, I already spent 2 years as an M.S. student at NYU, during which time I participated
in some research projects. Before coming to the U.S., I was an undergraduate student at the School of Computer Science and Technology,
Tianjin University, conducting research in computational photography advised by professor Shiguang
If you need more information, my resume is available by email.
- It can be confirmed that some datasets used in our article "Text Understanding from Scratch" have sample duplication issues. These issues include multiple instances of the same sample, and overlaps between training and testing data. For more information, please refer to my blog post.
Google Scholar profile
- Xiang Zhang, Yann LeCun. Text Understanding from Scratch. Arxiv 1502.01710. Datasets (more to come). Code. Dataset duplication issues.
- Pierre Sermanet, David Eigen, Xiang Zhang, Michaël Mathieu, Rob Fergus, Yann LeCun. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks. International Conference on Learning Representations 2014
- Shiguang Liu, Xiang Zhang. Image Colorization Based on Texture Map. Journal of Electronic Imaging, 2013, Volume 22, Issue 1, 01311
- Shiguang Liu, Xiang Zhang. Automatic Grayscale Image Colorization using Histogram Regression. Pattern Recognition Letters, 2012, Volume 33, Issue 13, Pages 1673-1681.
- Shiguang Liu, Hanqiu Sun, Xiang Zhang. Selective color transferring via ellipsoid color mixture map. Journal of Visual Communication and Image Representation, 2012, Volume 23, Issue 1, Pages 173-181.
- Xiang Zhang, Ce Yu. Fast n-point Correlation Function Approximation with Recursive Convolution for Scalar Fields. In IEEE Cloud Computing Technology and Science (CloudCom) CloudCom 2011, Pages 634-639.
- Xiang Zhang, Shiguang Liu, Texture Transfer in Frequency Domain. IEEE 2011 Sixth International Conference on Image and Graphics(ICIG), Pages 123-128.
- Shiguang Liu, Xiang Zhang, Jingting Wu, Jizhou Sun, Qunsheng Peng, Gray-scale Image Colorization based on the Control of Single-parameter. Journal of Image and Graphics (In Chinese), 2011, Volume 16(7), Pages 1297-1302.
Update April 9th 2015: In wake of dataset duplication issues for the Amazon reviews dataset, professor Julian McAuley updated their SNAP Amazon reviews dataset distribution webpage with an extra note and an extra data duplication file. On April 6th 2015, we discovered some issues related to the datasets used in our technical report “Text Understanding from Scratch”. These issues include multiple instances of the same sample, and overlaps between training and testing data.
Google’s April fool surprise: reading characters in reverse order (https://com.google/). It happened to be the case that the character order in Crepe (https://github.com/zhangxiangxiao/Crepe) is also reversed. The original thought was that aligning the end of a document to a fixed position (in this case at the beginning) could make it easier for the fully-connected layers to associate meaning with the ending context window. This may have the effect of biasing classification towards the end reading of a text, which has a somewhat distant relationship with how recurrent neural network representation can be used for classification, since it decays the influence of document at the beginning but not so much at the end.
This blog summarizes an answer I posted to a question regarding what kinds of research are there for deep learning, in Zhihu, a Chinese equivalence of Quora. Surprisingly, that answer drew a lot of attention from many students and young researchers in China and it is currently ranked the second best answer in the subcategory of “deep learning”. I hope the summarization here could offer my bit of thought to a broader audience by translating that answer to English.