Anna Ma, University of California (Irvine)

Title: The Kaczmarz Algorithm: Greed, Randomness, and Tensors.

Abstract: In settings where data sets become extremely large-scale, stochastic iterative methods such as the Kaczmarz algorithm and Randomized Coordinate Descent become advantageous due to their low memory footprint. The Randomized Kaczmarz algorithm in particular has garnered attention owing to its applicability in large-scale settings and its elegant geometric interpretation. In this talk, we will discuss the Randomized Kaczmarz algorithm, it's connection to the popular Stochastic Gradient Descent algorithm and it's greedy counter-part: Motzkin's Method. This presentation contains joint work with Jamie Haddock and Denali Molitor.

https://dms.umontreal.ca/~mathapp/index_fr.html

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