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CSE 40657/60657
Natural Language Processing

Term
Spring 2021
Time
MWF 1–1:50pm
Room
Fitzpatrick 356 / Zoom 99113952531
Instructor
David Chiang

Computers process massive amounts of information every day in the form of human language. Although they do not understand it, they can learn how to do things like answer questions about it, or translate it into other languages. This course is a systematic introduction to the ideas that form the foundation of current language technologies and research into future language technologies.

The official prerequisites are CSE 20312 or CDT 30020. Students should be experienced with writing substantial programs in Python. The course also makes use of finite automata, context-free grammars, basic linear algebra, multivariable differential calculus, and probability theory. Ideally, students should have taken CSE 30151, Math 10560, and ACMS 30440, but please contact the instructor if you have questions about the necessary background.

Staff

The best way to contact the teaching staff is on Piazza.

Instructor
Prof. David Chiang
Office hours: TTh 1-2pm
Zoom 99113952531
Teaching assistant
Toan Nguyen
Office hours: Wed 7-9pm
Zoom 99113952531

Schedule

I'm revising the schedule for 2021 more extensively than usual. The general plan is stable, but the day-to-day topics are subject to change.

Unit Week Assignment Mon Wed Fri
Foundations 1 Chapter 1
Project idea (due 02/12)
02/03
Language
02/05
Probability
2 Chapter 2
02/08
N-gram language models
02/10
Overfitting and regularization
02/12
Weighted automata
3 HW1: Text prediction (due 02/26)
02/15
RNNs: motivation
02/17
RNNs: definition
02/19
RNNs: training
4 Chapter 3
02/22
IBM Model 1 and 2
02/24
Training the IBM models
02/26
Attention
5 HW2: Machine translation (due 03/12)
03/01
NMT: motivation
03/03
NMT: RNNs
03/05
NMT: Transformers
Inputting Language 6
03/08
Phonetics and phonology
03/10
Speech recognition
03/12
Writing systems and character/handwriting recognition
Analyzing Language 7 Project baseline (due 03/26)
03/15
Morphology
03/17
Part-of-speech tagging
03/19
Conditional random fields
8
03/22
Syntax
03/24
Context-free grammars
03/26
CKY parsing
9 HW3: Parsing (due 04/09)
03/29
Neural parsing
03/31
Beyond CFGs
04/02
Good Friday
Understanding Language 10
04/05
Bags of words; topic models
04/07
Word embeddings
04/09
Projects
11 HW4: Entity recognition (due 04/23)
04/12
Recognizing entities and relations
04/14
Graph semantics and graph grammars
04/16
Projects
12
04/19
Logical semantics
04/21
Mini-break
04/23
Projects
Generating Language 13 HW5: Generation (due 05/07)
04/26
Unconstrained generation
04/28
Generating from vectors
04/30
Projects
14
05/03
Generating from graphs
05/05
Generating from logical forms
05/07
Projects
15 Project report (due 05/18)
05/10
Conclusion

Requirements

Your work in this course consists of five homework assignments and a research project.

All written work should be submitted through Sakai.

requirement points
homeworks 5 × 30
project 3 × 30 + 60
total 300
letter gradepoints
A 280–300
A− 270–279
B+ 260–269
B 250–259
B− 240–249
C+ 230–239
C 220–229
C− 210–219
D 180–209
F 0–179

Policies

Honor Code

Students in this course are expected to abide by the Academic Code of Honor Pledge: “As a member of the Notre Dame community, I will not participate in or tolerate academic dishonesty.”

The following table summarizes how you may work with other students and use print/online sources:

Resources Solutions
Consulting allowed not allowed
Copying cite not allowed
See the CSE Guide to the Honor Code for definitions of the above terms.

If an instructor sees behavior that is, in his judgement, academically dishonest, he is required to file either an Honor Code Violation Report or a formal report to the College of Engineering Honesty Committee.

Late Submissions

In the case of a serious illness or other excused absence, as defined by university policies, coursework submissions will be accepted late by the same number of days as the excused absence. Otherwise, you may submit part of an assignment on time for full credit and part of the assignment late with a penalty of 30% per week (that is, your score for that part will be $\lfloor 0.7^t s\rfloor$, where $s$ is your raw score and $t$ is the possibly fractional number of weeks late). No part of the assigment may be submitted more than once. No work may be submitted after the final project due date.

Students with Disabilities

Any student who has a documented disability and is registered with Disability Services should speak with the professor as soon as possible regarding accommodations. Students who are not registered should contact the Office of Disability Services.