This course is taken almost verbatim from CS 224D Deep Learning for Natural Language Processing -- Richard Socher's course at Stanford. We are following their course's formulation and selection of papers, with the permission of Socher.
This is a section of the CS 6101 Exploration of Computer Science Research at NUS. CS 6101 is a 4 modular credit pass/fail module for new incoming graduate programme students to obtain background in an area with an instructor's support. It is designed as a "lab rotation" to familiarize students with the methods and ways of research in a particular research area.
Our section will be conducted as a group seminar, with class participants nominating themselves and presenting the materials and leading the discussion. It is not a lecture-oriented course and not as in-depth as Socher's original course at Stanford, and hence is not a replacement, but rather a class to spur local interest in Deep Learning for NLP. Unlike the original course, there are no projects, assignments or homework, although you would certainly get more out of the topic if you did them.
This "course" is offered twice, for Session I (Weeks 3-7)and Session II (Weeks 8-13), although it is clear that the course is logically a single course that builds on the first half. Nevertheless, the material should be introductory and should be understandable given some prior study.
A discussion group will be on Slack . Students and guests, please login when you are free. If you have a .comp.nus.edu.sg email address you can create your Slack account for the group discussion without needing an invite.
18:00-20:00, Tuesdays for Session I (Weeks 3-7). Venue is SR2 (COM1 #02-04).
18:00-20:00, Mondays for Session II (Weeks 8-13). Venue is SR10 (COM1 #02-10).
For directions to NUS School of Computing (SoC) and COM1: please read the directions here, to park in CP13 and/or take the bus to SoC. and use the floorplan to find SR2 and SR10.
Please eat before the course or during (we don't mind -- like a brown-bag-seminar series), and if you're parked, you will be able to leave after 7:30pm without paying carpark charges.
Welcome. If you are an external visitor and would like to join us, please email Kan Min-Yen to be added to the class role. Guests from industry, schools and other far-reaching places in SG welcome, pending space and time logistic limitations. The more, the merrier.
External guests will be listed here in due course once the course has started. Please refer to our Slack after you have been invited for the most up-to-date information.
NUS (Postgraduate): Session I (Weeks 3-7): Cai Shaofeng, Feng Piaopiao, Lim Xiang Hui Nicholas, Wang Kailong, Wang Taining
NUS (Postgraduate): Session II (Weeks 8-13): Tang Yixuan, Wang Yan, Yang Lin, Yang Yueji
NUS (Undergraduate): Edward Elson, Yap Jia Qing
WING: Muthu Kumar Chandrasekaran, Tao Chen, Xiangnan He, Min-Yen Kan, Manpreet Kaur, Lei Wenqiang, Animesh Prasad, Su Xuan, Kazunari Sugiyama, Chencan Xu
Guests: Ashutosh Gaur, Hitoshi Iwasaki, Phu Mon Htut, Nicolas Lim, Minh Nguyen, Shubham Goyal (www.holmusk.com), Lee Yi Jie Joel, Edwin Tam, Samdish Suri, Kristin Nguyen, Umamaheswari Vasanthakumar, Lonce Wyse
|Week 3 (Week of 22 Aug)|
Tue, 23 Aug, 18:00-20:00
|Intro to NLP and Deep Learning|
|Week 4 (Week of 29 Aug)|
Tue, 30 Aug, 18:00-20:00
|Simple Word Vector representations: word2vec, GloVe|
Presenters/Questioners: Wang Taining, Phu Mon Htut, Manpreet Kaur, Kristin Nguyen, Cheng Yong, Yi Chiao Cheng