Mathematics
Te Tari Pāngarau me te Tatauranga
Department of Mathematics & Statistics

Upcoming seminars in Mathematics

Research seminars
Seminars in Statistics
The changing face of undergraduate mathematics education: a US perspective

Rachel Weir

Allegheny College, Pennsylvania

Date: Monday 16 October 2017
Time: 2:00 p.m.
Place: Room 241, 2nd floor, Science III building

Note day and time of this seminar
A common theme in the United States in recent years has been a call to increase the number of graduates in STEM (science, technology, engineering, and mathematics) fields and to enhance the scientific literacy of students in other disciplines. For example, in the 2012 report Engage to Excel, the Obama administration announced a goal of "producing, over the next decade, 1 million more college graduates in STEM fields than expected under current assumptions." Achieving these types of goals will require us to harness the potential of all students, forcing us to identify and acknowledge the barriers encountered by students from traditionally underrepresented groups. Over the past few years, I have been working to understand these barriers to success, particularly in mathematics. In this talk, I will share what I have learned so far and how it has influenced my teaching.
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Why does the stochastic gradient method work?

Matthew Parry

Department of Mathematics and Statistics

Date: Tuesday 24 October 2017
Time: 2:00 p.m.
Place: Room 241, 2nd floor, Science III building

The stochastic gradient (SG) method seems particularly suited to the numerical optimization problems that arise in large-scale machine learning applications. In a recent paper, Bottou et al. give a comprehensive theory of the SG algorithm and make some suggestions as to how it can be further improved. In this talk, I will briefly give the background to the optimization problems of interest and contrast the batch and stochastic approaches to optimization. I will then give the mathematical basis for the success of the SG method. If time allows, I will discuss how the SG method can also be applied to sampling algorithms.
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Tom ter Elst

University of Auckland

Date: Tuesday 31 October 2017
Time: 2:00 p.m.
Place: Room 241, 2nd floor, Science III building

Title and abstract to follow
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Vee Liem Saw

Department of Mathematics and Statistics

Date: Tuesday 7 November 2017
Time: 2:00 p.m.
Place: Room 241, 2nd floor, Science III building

Title and abstract to follow
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Jonny Williams

National Institute of Water and Atmospheric Research (NIWA)

Date: Wednesday 15 November 2017
Time: 2:00 p.m.
Place: Room 241, 2nd floor, Science III building

Note day and time of this seminar
A joint seminar with the Department of Physics
Title and abstract to follow
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