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Department of Mathematics,
Department of Mathematics,
University of California San Diego
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Math 288: Probability & Statistics
Rob Webber
UCSD
How fast is square volume sampling Kaczmarz?
Abstract:
Randomized Kaczmarz (RK) is a well-known solver for linear least-squares problems. RK iteratively processes blocks of rows in order to update an approximation to the least-squares solution. Recent work suggests that RK converges rapidly when each block of rows is sampled from the square volume distribution defined by the target matrix. Additionally, there are reports of accelerated convergence when the RK iterates produced in the tail part of the algorithm are averaged together. I will clarify the theoretical convergence guarantees for square volume sampling Kaczmarz both with and without tail-averaging.
October 30, 2025
11:00 AM
APM 6402
Research Areas
Probability Theory Statistics****************************
