##### Department of Mathematics,

University of California San Diego

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### Center for Computational Mathematics Seminar

## Anna Ma

#### UCSD

## Variants of the Randomized Kaczmarz Algorithm and its Applications

##### Abstract:

Nowadays, data is exploding at a faster rate than computer architectures can handle. For that reason, mathematical techniques to analyze large-scale data need be developed. Stochastic iterative algorithms have gained interest due to their low memory footprint and adaptability for large-scale data. In this talk, we will present the Randomized Kaczmarz algorithm for solving extremely large linear systems of the form Ax=y. In the spirit of large-scale data, this talk will act under the assumption that the entire data matrix A cannot be loaded into memory in a single instance. We consider different settings including when a only factorization of A is available, when A is missing information, and a time-varying model. We will also present applications of these Kaczmarz variants to problems in data science.

### December 4, 2018

### 10:00 AM

### AP&M 2402

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