CSE 291:
Robust Statistics

Fall 2023

**Announcements:**

- First day of class September 29th
- Sorry, I missed the first day due to jury duty, but the
rest of the lectures should happen as scheduled.

**Homeworks: **

- Homework 1: Due in class Friday October 13th
- Do two of the following textbook exercises: 1.3, 1.5, 1.6, 1.7a&b, 1.8, 1.9a&b, 1.9c&d, 1.11, 1.12b&c
- Homework 2: Due in class on Friday October 27th
- Do two of the following textbook exercises: 2.2, 2.3, 2.4, 2.6, 2.7, 2.9, 2.11
- Homework 3: Due in class on Monday November 13th
- Do two of the following textbook exercises: 3.4, 3.5, 3.8, 5.1, 5.2, 5.3, 5.7, 5.8
- Homework 4: Due in class on Wednesday November 29th
- Do two of the following textbook exercises: 6.2, 6.3,
6,4, 6.5, 7.2, 7.3, 7.4, 7.5

**Other: **

- Course Syllabus
- Course Textbook can be found online here.
Hard copy can be purchased here.

- Lecture Podcasts

**Course
Description**: Most standard statistical estimators fail
badly when faced with even a few extreme outliers. While naive
outlier removal techniques can often solve this problem in low
dimensions, the performance of such techniques degrades badly
for higher dimensional problems. Until recently all known
techniques for solving even simple statistical problems either
produced errors scaling polynomially in the dimension or
runtimes that were exponential in it. CSE 291 covers some
recent breakthroughs in the field of computational statistics
for the first time leading to practical solutions to many of
these problems.