Seminar in Statistics: High-dimensional Statistics

Short Description:

The seminar familiarizes students with the basic techniques of high-dimensional data analysis. Both theoretical concepts and practical implementation of methods will be discussed.

Prerequisites:

We require at least one course in statistics in addition to the 4th semester course Introduction to Probability and Statistics.

Program:

The schedule is available here (last updated 17.2.)

Terms and conditions:

Each student is required to hold a presentation about a given subject. We allow 2 students per class who present ca. 60 minutes in total. Each group will coordinate their oral contributions. Additionally, students should be present at the other seminar classes.

Two weeks prior to the presentation date each student attends a meeting with one of the assistants to discuss the topic and discuss remaining questions. Standard time for this first meeting is Monday 13:45 at the advisor's office. It is expected that the student has already read the material and is familiar with the topic. One week prior to the presentation each student meets again with the same assistant (they have to agree on a time). It is expected that presentation and handout (optional) are more or less finished. Both meetings will take place either on Mondays or Tuesdays.

We regard feedback as an important part of such a seminar. Rules for giving and receiving feedback can be found here, criteria for feedback can be found here. Take your talk number add 4 and consider the result modulo 12. This is when your group is supposed to give feedback.

Ask many questions! Take your talk number, substract 4 and consider the result modulo 12. This is, when you are supposed to ask questions. You do not have to prepare anything for this but each member of your group has to ask at least one question. You are encouraged to ask questions during other talks, too, of course.

Literature:

• The seminar is based on a selection of papers on basic techniques in high-dimensional statistics. The material for each topic may be found in the schedule under the program.
  
• For an additional overview of theory, methods and algorithms in high-dimensional statistics, see
  "Statistics for high-dimensional data: methods, theory and applications" by P. Bühlmann and S. van de Geer, Springer (2011)

The book is available online via the ETH library.

Guidelines for the Presentation:

• Use examples and pictures.
• There is a break of ca. 5 minutes if there is more than one talk on a day.
• You are responsible for scheduling your presentation. Including a discussion at the end (5 minutes), you should not go over 60 minutes.
  
• After the presentation there will be feedback (5 minutes).
• Look at other sources (books, papers, internet) to gain even more knowledge about your topic.