RSS FeedUpcoming EventsProbability seminar: An elementary approach to non-asymptotic random matrix theory for unitarily invariant matrices, March 20https://events.berkeley.edu/live/events/240846-probability-seminar-jorge-garza-vargas

Classical random matrix theory focuses on the study of highly structured models (e.g. Wigner and Wishart matrices) which are presented as a sequence of random matrices defined for every dimension, whose asymptotic (i.e. as the dimension goes to infinity) spectral properties must be understood in detail. However, modern problems in data and computer science require only a coarser understanding of the random matrices in question, but necessitate nonasymptotic results in settings where the models are less structured and do not necessarily belong to a prescribed sequence of matrices.

In this work we provide new tools for analyzing the spectral distribution of self-adjoint noncommutative polynomials evaluated in arbitrary independent unitarily invariant Hermitian random matrices of a fixed dimension. With these tools we are able to recover some of Parraud’s results which quantify the distance of the spectral distribution of random matrices with the aforementioned structure from the spectral distribution of their free (in the sense of free probability) limit.


This is joint work with Chi-Fang Chen and Joel Tropp.

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Probability seminar: Benjamin McKenna, April 3https://events.berkeley.edu/live/events/240876-probability-seminar-benjamin-mckenna

TBA

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Stat/EPS Joint Seminar, April 8https://events.berkeley.edu/stat/event/243182-stateps-joint-seminar

Join us for an informal workshop on open statistical problems in the earth and planetary sciences!

https://events.berkeley.edu/stat/event/243182-stateps-joint-seminar
Probability seminar: Hao Wu, April 10https://events.berkeley.edu/live/events/240849-probability-seminar-hao-wu

TBA

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Stat/EPS Joint Seminar, April 22https://events.berkeley.edu/stat/event/243278-stateps-joint-seminar

Join us for an informal workshop on open statistical problems in the earth and planetary sciences!

https://events.berkeley.edu/stat/event/243278-stateps-joint-seminar
Probability seminar: Wai Tong (Louis) Fan, April 24https://events.berkeley.edu/live/events/240850-probability-seminar-wai-tong-louis-fan

TBA

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Probability seminar: Adam Jaffe, May 1https://events.berkeley.edu/live/events/243044-probability-seminar-adam-jaffe

TBA

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Inaugural Berkeley-Stanford Workshop on Veridical Data Science, May 31https://events.berkeley.edu/live/events/239397-inaugural-berkeley-stanford-workshop-on-veridical

The Berkeley-Stanford Veridical Data Science Workshop is focused on showcasing and promoting veridical (truthful) data science (VDS) for reproducible, reliable data analysis and decision-making. It intends to build a community of veridical data science researchers for trustworthy data science, machine learning, and artificial intelligence. The discussions will promote opportunities for statisticians and data scientists to identify important VDS research topics and critical applications in academia and industry. Graduate students and early career researchers will benefit from this conference to find future research directions.

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Organizing Committee:
Bin Yu (UC Berkeley, co-chair), Russ Poldrack (Stanford University, co-chair), Maya Mathur (Stanford University), and Tiffany Tang (University of Michigan)

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