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Lectures on Randomized Numerical Linear Algebra

arXiv 1712.08880 ↗First posted 24 Dec 2017cs.DS stat.MLcited by 19

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Abstract (arXiv)

This chapter is based on lectures on Randomized Numerical Linear Algebra from the 2016 Park City Mathematics Institute summer school on The Mathematics of Data.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Dec 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 2; 2023: 5; 2024: 4; 2025: 2; 2026: 4.

19 papers.

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  1. 2023Full Stack Optimization of Transformer Inference: a Surveycited by 79
  2. 2021Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Updatecited by 23
  3. 2024Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learningcited by 11
  4. 2023Sketched Ridgeless Linear Regression: The Role of Downsamplingcited by 7
  5. 2022Sketch-and-Lift: Scalable Subsampled Semidefinite Program for K-means Clusteringcited by 6
  6. 2023Feature Space Sketching for Logistic Regressioncited by 4
  7. 2026PRISM: Distribution-free Adaptive Computation of Matrix Functions for Accelerating Neural Network Trainingcited by 4
  8. 2024Efficient Backpropagation with Variance-Controlled Adaptive Samplingcited by 3
  9. 2024Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Valuescited by 2
  10. 2026Quantifying Epistemic Uncertainty in Diffusion Modelscited by 2
  11. 2026Improved large-scale graph learning through ridge spectral sparsificationcited by 2
  12. 2021Toeplitz Least Squares Problems, Fast Algorithms and Big Datacited by 1
7 more
  1. 2023SALSA: Sequential Approximate Leverage-Score Algorithm with Application in Analyzing Big Time Series Datacited by 1
  2. 2024A Provably Accurate Randomized Sampling Algorithm for Logistic Regressioncited by 1
  3. 2025Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newtoncited by 1
  4. 2022On confidence intervals for precision matrices and the eigendecomposition of covariance matricescited by 0
  5. 2023On the Noise Sensitivity of the Randomized SVDcited by 0
  6. 2025Importance Sampling for Nonlinear Modelscited by 0
  7. 2026The Advantages of Fresh Sketching for Ridge Regressioncited by 0