This research-led course provides an introduction to recent developments in Random Matrix Theory and Online Learning that addresses the challenges and opportunities posed by the availability of large amounts of data.

In the first instance, we will review some classic results from multivariate statistical theory, matrix analysis, and probability theory. Then we will present the salient statistical features of big data (e.g., heterogeneity, noise accumulation, spurious correlation, and incidental endogeneity) and show how this impacts on traditional statistical methods and theory.

We follow with an introduction to modern Random Matrix theory and its application in statistics. Applications presented may include topics such as high-dimensional statistical inference, large covariance matrices, large-scale statistical learning through subsampling, sparsification of large matrices, principal component analysis, and dimension reduction.

We conclude with an introduction to the theory of online learning (aka. sequential prediction) to handle the situation of streaming data.

The weekly 2-hour lectures will be accompanied by a 1-hour practical workshop where students will use and learn about the latest computational tools to work with big and streaming data sets. Example data sets may be drawn from areas such finance, web analytics, digital marketing, and satellite imagery data.

Research-Led Teaching

This course is solely largely based on recent research papers and surveys on the topic of random matrices in statistics. The topic is rapidly advancing and recent results may be introduced into the course as they appear in the literature.  

Required Resources

None. Resources (research papers, etc) and lecture notes will be provided throughout the semester.

Staff Feedback

Students will be given feedback in the following forms in this course:

• Written comments
• Verbal comments
• Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Introduction to the challenges of Big Data and overview of the course. Review of some prerequisite concepts.
2	Further matrix analysis, eigenvalues and eigenvectors, the multivariate normal distribution.
3	Fundamental tools for studying limiting spectral distributions, Marcenko-Pastur distributions, Fisher spectral distribution.	Homework 1
4	CLT for linear spectral statistics: Introduction and integration tools.
5	Moments and statistics of the Marcenko-Pastur distribution.
6	CLT for linear spectral statistics: Sample covariance matrix, Bai and Silverstein’s CLT, CLT for random Fisher matrices.	Homework 2
7	Generalised variance in higher dimensions.
8	Multiple correlation coefficient.
9	Multivariate linear regression in the high-dimensional setting.	Homework 3
10	PCA and high-dimensional spiked population models.
11	Applications and recent theoretical results.
12	Applications and recent theoretical results.	Final Project

Tutorial Registration

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle or during your first lecture. When tutorials are available for enrolment, follow these steps:

 

1.   Log on to Wattle, and go to the course site

2.   Click on the link ‘Tutorial enrolment’

3.   On the right of the screen, click on the tab ‘Become Member of . . . .’ for the tutorial class you wish to enter

 

 

4.   Confirm your choice

 

If you need to change your enrolment, you will be able to do so by clicking on the tab ‘Leave group. . . .’ and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number. Please note that enrolment in ISIS must be finalised for you to have access to Wattle.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Homework 1	15 %	09/08/2019	23/08/2019	1-2
Homework 2	15 %	30/08/2019	16/09/2019	1-4,6,7
Homework 3	15 %	04/10/2019	18/10/2019	1-7
Final Project	55 %	01/11/2019	28/11/2019	1-7

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

• Student Assessment (Coursework) Policy and Procedure
• Special Assessment Consideration Policy and General Information
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Examination(s)

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule. The homeworks and final project must be done individually, any similarities between results will be investigated under the University’s Academic Misconduct Rule.

Assessment Task 1

Homework 1

The homework tasks will be small take-home assessments that will typically involve one ‘pen-and-paper’ question and/or a ‘computational’ question. The question(s) will cover material that has been seen in previous lectures and are aimed at ensuring students are routinely studying the material. The Homework questions will be released two weeks before the due date. The assessment will be submitted in Wattle using TurnitIn by 23:59 on the due date and marks/feedback will be given on the 'Return of Assessment Date'.

Assessment Task 2

Homework 2

The homework tasks will be small take-home assessments that will typically involve one ‘pen-and-paper’ question and/or a ‘computational’ question. The question(s) will cover material that has been seen in previous lectures and are aimed at ensuring students are routinely studying the material. The Homework questions will be released two weeks before the due date. The assessment will be submitted in Wattle using TurnitIn by 23:59 on the due date and marks/feedback will be given on the 'Return of Assessment Date'.

Assessment Task 3

Homework 3

The homework tasks will be small take-home assessments that will typically involve one ‘pen-and-paper’ question and/or a ‘computational’ question. The question(s) will cover material that has been seen in previous lectures and are aimed at ensuring students are routinely studying the material. The Homework questions will be released two weeks before the due date. The assessment will be submitted in Wattle using TurnitIn by 23:59 on the due date and marks/feedback will be given on the 'Return of Assessment Date'.

Assessment Task 4

Final Project

The final project will be a mix of theoretical and computational tasks. The project will focus on either a recent research paper or a particular theme/application. The Final Project will be released 4 weeks before the due date. The assessment will be submitted in Wattle using TurnitIn by 23:59 on the due date and marks/feedback will be given on the 'Return of Assessment Date'. Projects will not be returned.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded. OR Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Assignment will be returned online.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Assignments may not be resubmitted.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents undergraduate and ANU College students
• PARSA supports and represents postgraduate and research students