Go to| Kobus Barnard 's seminar page | Kobus Barnard 's Home Page

Mathematical methods seminar

This meeting is for in-depth reading and discussion of mathematical methods applicable to computer vision and machine learning. Usually a reading is assigned each week, and the meetings are used to review and discuss the reading. Previous topics have included measure theory, group theory, and hamiltonian mechanics.

Everyone welcome!

If you wish to recieve mail regarding this seminar and related topics, please subscribe to the COMPVISLAB-MATH mailing list. Instructions for subscribing to UA lists can be found here.

Spring 2009

Group meets on Wednesdays, 2:30-4:00. First topic will be stochastic dynamics, followed by stochastic processes in general. Schedule is below.

Date	Topic	Discussion Leader
Jan 20	Hamiltonian Mechanics	TBD
Jan 27	Hamiltonian Mechanics (ctd)	TBD
Feb 3	Sampling review / Stochastic Dynamics	TBD
Feb 10	Stochastic Dynamics (ctd.)	TBD
Feb 17	Hybrid Monte Carlo Algorithm	TBD
Feb 24	Hybrid Monte Carlo Algorithm (ctd) (?)	TBD

Fall 2009

In the Fall of 2009, we studied group theory, with the goal of understanding wreath products and their application in the book "A Generative Theory of Shape" by Michael Leyton. We read from Jim Howie's lecture notes on group theory. The group met on Wednesdays from 3-4:30.

Summer 2009

During the summer of 2009, we studied measure theory, including Lebesque integration. We used lecture notes by Davar Khoshnevisan, which he calls "Mathematical Probability," specifically chapters 1, 2, 3 and 5. Other supplemental readings were:

"A Probability Path" by Sidney Resnick
Measure Theory and Integration lecture notes by Bath
"Measure Theory, Integration & Probability" by Ivan Wilde