Playlist: 28 videos

Randomized Numerical Linear Algebra and Applications

0:34:32

Convergence Theory for Iterative Eigensolvers

Mark Embree (Virginia Tech University)
https://simons.berkeley.edu/talks/convergence-theory-iterative-eigensolvers
Randomized Numerical Linear Algebra and Applications
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0:34:57

Randomized Algorithms for Computing Full Matrix Factorizations

Gunnar Martinsson (University of Texas at Austin)
https://simons.berkeley.edu/talks/randomized-algorithms-computing-full-matrix-factorizations
Randomized Numerical Linear Algebra and Applications
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0:29:14

Applying Randomized Methods for Zonotope Enumeration and Monte Carlo Methods for Solving Linear Systems

David Gleich (Purdue University)
https://simons.berkeley.edu/talks/applying-randomized-methods-zonotope-enumeration-and-monte-carlo-methods-solving-linear
Randomized Numerical Linear Algebra and Applications
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0:34:22

Error Estimation for Randomized Numerical Linear Algebra: Bootstrap Methods

Miles Lopes (UC Davis)
https://simons.berkeley.edu/talks/error-estimation-randomized-numerical-linear-algebra-bootstrap-methods
Randomized Numerical Linear Algebra and Applications
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0:43:32

Scalable Algorithmic Primitives for Data Science

Richard Peng (Georgia Institute of Technology)
https://simons.berkeley.edu/talks/scalable-algorithmic-primitives-data-science
Randomized Numerical Linear Algebra and Applications
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0:33:27

Hessian Matrix Inversion in 10^10 Dimensions with Parametric Bootstraps

Uros Seljak (UC Berkeley)
https://simons.berkeley.edu/talks/hessian-matrix-inversion-1010-dimensions-parametric-bootstraps
Randomized Numerical Linear Algebra and Applications
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0:31:49

Ridge Regression and Deterministic Ridge Leverage Score Sampling

Shannon McCurdy (UC Berkeley)
https://simons.berkeley.edu/talks/ridge-regression-and-deterministic-ridge-leverage-score-sampling
Randomized Numerical Linear Algebra and Applications
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0:31:26

Large Scale Stochastic Training of Neural Networks

Amir Gholaminejad (UC Berkeley)
https://simons.berkeley.edu/talks/large-scale-stochastic-training-neural-networks
Randomized Numerical Linear Algebra and Applications
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0:27:56

Randomized Constrained Matrix Decompositions

Benjamin Erichson (University of Washington)
https://simons.berkeley.edu/talks/randomized-constrained-matrix-decompositions
Randomized Numerical Linear Algebra and Applications
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0:32:8

Adventures with Randomized Algebra for Extreme-Scale Signal Processing

Anshumali Shrivastava (Rice University)
https://simons.berkeley.edu/talks/adventures-randomized-algebra-extreme-scale-signal-processing
Randomized Numerical Linear Algebra and Applications
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