Spring 2017 CS292F Deep Learning for NLP

Instructor and Venue

• Instructor: William Wang
• TA: TBA
• Time: T R 1:00pm - 2:50pm
• Location: PHELPS 2510
• TA Office Hours: TBA
• Instructor Office Hours: Tu 3-4pm HFH 1115
• Prerequisites:
  • Good programming skills and knowledge of data structure (e.g., CS 130A)
  • Solid background in machine learning, linear algebra, probability, and calculus.
  • Comfortable with deep learning platforms such as TensorFlow, Torch, Theano, MXNet, Caffe etc.
  • Prior experiences with AWS is not required, but could be very useful.

Course Objective

At the end of the quarter, students should have a good understanding about basic NLP tasks, and should be able to implement some fundamental algorithms for simple problems in NLP. Students will also develop an understanding of the open research problems in NLP.

Piazza

TBA

Syllabus

TBA

Course Description

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Text Book

TBA

Grading

There will be two homework assignments (20%), one project (65%), and an in-class midterm exam (15%). The breakdown of project grading includes: proposal (10%), mid-term presentation (10%), final presentation (15%), and a final report (30%). Four late days are allowed with no penalty. After that 50% will be deducted if it is within 4 days after the due day, unless you have a note from the doctors' office. Homework assignment submissions that are five days late will receive zero credits.

Final Report Format

You must use the ICML 2017 latex style files for writing the report. The final report must be 4-8 pages long. It is encouraged to include the following components in your report: abstract, introduction (motivation, task definition, your novel contributions), related work, your approach, experiments, discussion, and conclusion.

Academic Integrity

We follow UCSB's academic integrity policy from UCSB Campus Regulations, Chapter VII:``Student Conduct and Discipline"):

• It is expected that students attending the University of California understand and subscribe to the ideal of academic integrity, and are willing to bear individual responsibility for their work. Any work (written or otherwise) submitted to fulfill an academic requirement must represent a student’s original work. Any act of academic dishonesty, such as cheating or plagiarism, will subject a person to University disciplinary action. Using or attempting to use materials, information, study aids, or commercial “research” services not authorized by the instructor of the course constitutes cheating. Representing the words, ideas, or concepts of another person without appropriate attribution is plagiarism. Whenever another person’s written work is utilized, whether it be a single phrase or longer, quotation marks must be used and sources cited. Paraphrasing another’s work, i.e., borrowing the ideas or concepts and putting them into one’s “own” words, must also be acknowledged. Although a person’s state of mind and intention will be considered in determining the University response to an act of academic dishonesty, this in no way lessens the responsibility of the student.

More specifically, we follow Stefano Tessaro and William Cohen's policy in this class:

You cannot copy the code or answers to homework questions or exams from your classmates or from other sources; You may discuss course materials and assignments with your classmate, but you cannot write anything down. You must write down the answers / code independently. The presence or absence of any form of help or collaboration, whether given or received, must be explicitly stated and disclosed in full by all involved, on the first page of their assignment. Specifically, each assignment solution must start by answering the following questions:

• (1) Did you receive any help whatsoever from anyone in solving this assignment? Yes / No.
  • If you answered 'yes', give full details: (e.g. ``Jane explained to me what is asked in Question 3.4")
• (2) Did you give any help whatsoever to anyone in solving this assignment? Yes / No.
  • If you answered 'yes', give full details: (e.g. ``I pointed Joe to section 2.3 to help him with Question 2".
• No electronics are allowed during exams, but you may prepare an A4-sized note and bring it the exam.
• If you have questions, often ask the teaching staff.

Academic dishonesty will be reported to the highest line of command at UCSB. Students who engage in such activities will receive an F grade automatically.

Accessibility

Students with documented disability are asked to contact the DSP office to arrange the necessary academic accommodations.

Discussions

All discussions and questions should be posted on our course Piazza site.