Events in MathSys and Complexity Science
This is a calendar page detailing events within the MathSys CDT. It also acts as a booking diary for the Seminar Room D1.07. To book D1.07 please email Sheetal.Sharma@warwick.ac.uk
Please note that your event booking is for D1.07 only. The adjacent common room is a private area for the MathSys Centre that cannot used as part of your booking.
MathSys CDT events have priority for D1.07 room bookings.
Click here to see all seminars taking place in the Mathematics InstituteLink opens in a new window
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MCMC using lessons from CSE
(Or: sample-based inference in large-scale inverse problems using
algorithms developed for computational optimization)
By Colin Fox
Abstract:
The Metropolis (Hastings-Green) algorithm for MCMC was invented in the
1950’s and has changed little since. In contrast, algorithms for
optimization that were also invented in the 1950’s have seen dramatic
improvement. We look to steal the developments in computational
optimization and apply them to sampling of probability distributions.
The connection between sampling and optimization is already close. For
example, Gibbs sampling of Gaussian distributions is exactly Gauss-Seidel
solution of linear equations – the iteration operators are identical and
convergence factors are identical. Polynomial acceleration developed for
iterative solvers can also accelerate Gibbs sampling giving optimal
convergence.
I will show some applications in large-scale inverse problems that
motivated this (ongoing) work, including sample-based inference in image
deblurring with non-negativity constraints computed using a sampling
version of the gradient-projected conjugate gradient algorithm.
organised by Andrew Stuart
LUNCH TO BE SERVED IN COMPLEXITY's COMMON ROOM
More…