# Lecture Notes on Randomized Linear Algebra

arXiv: https://arxiv.org/abs/1608.04481 · HTML: https://mlsanity.com/paper/1608.04481/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Aug 2016.

## Built on by (most cited first, 11 of 11)

- [Matrix Compression via Randomized Low Rank and Low Precision Factorization](https://mlsanity.com/paper/2310.11028/) (2023)
- [Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning](https://mlsanity.com/paper/2406.11151/) (2024)
- [Efficient Sketches for Training Data Attribution and Studying the Loss Landscape](https://mlsanity.com/paper/2402.03994/) (2024)
- [GraSS: Scalable Data Attribution with Gradient Sparsification and Sparse Projection](https://mlsanity.com/paper/2505.18976/) (2025)
- [Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds](https://mlsanity.com/paper/2203.09755/) (2022)
- [Randomized Algorithms for Symmetric Nonnegative Matrix Factorization](https://mlsanity.com/paper/2402.08134/) (2024)
- [Quantum Machine Learning For Classical Data](https://mlsanity.com/paper/2105.03684/) (2021)
- [Gradient Coding with Iterative Block Leverage Score Sampling](https://mlsanity.com/paper/2308.03096/) (2023)
- [Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers](https://mlsanity.com/paper/2108.05969/) (2021)
- [Oversampling Divide-and-conquer for Response-skewed Kernel Ridge Regression](https://mlsanity.com/paper/2107.05834/) (2021)
- [Iterative Sketching for Secure Coded Regression](https://mlsanity.com/paper/2308.04185/) (2023)

## Abstract (arXiv)

These are lecture notes that are based on the lectures from a class I taught on the topic of Randomized Linear Algebra (RLA) at UC Berkeley during the Fall 2013 semester.