Ryan Anderson Presents the 5th Annual Ryan Anderson Williamsburg MLK Pub Crawl Extravaganza
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First crawl of the Biden admin so you know we’re doing it Scranton-style.
Posts by Collection
personal
6th Annual Ryan Anderson Williamsburg MLK Pub Crawl Extravaganza
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When unremarkable Virginians conducted a raiding mission under George Washington’s leadership, the world could not have foreseen what would come. Here we sit at the same distance from the first RAWMLKPCE.
Return of the Ryan Anderson Williamsburg MLK Pub Crawl Extravaganza
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Like the Gulf War, the 2025 edition of the RAWMLKPCE did not take place. Will 2026 be different? The answer lies in your heart, reader.
portfolio
High-Dimensional Statistics Notes
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High-dimensional statistics is the branch of statistics concerned with obtaining bounds on how random variables differ from their expectations, especially as the number of dimensions in the data increases. These notes will tackle three topics: (1) basic concentration inequalities and properties of sub-Gaussian random variables, (2) sparse linear regression, and (3) Dudley’s theorem and its applications.
Numerical Analysis Notes
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This page relates notes from MATH 269A at UCLA, numerical analysis.
Introduction to Reinforcement Learning Notes
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Table of Contents
Real Analysis III
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Lecture 3/31: Measure and Integration on Topological Spaces in General
We construct a chain of concepts in real analysis, beginning with the Borel $\sigma$-algebra $\mathbb{B}$ which is the $\sigma$-algebra on $\mathbb{R}^n$ generated by all open sets.
publications
talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Introduction to Grobner Bases with Applications to the Geometry of Value Functions
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In this talk I described the application of the theory of Grobner bases and elimination to the problem of finding the boundary of the space of value functions in reinforcement learning.
The Geometry of the Space of Value Functions in POMDPs via Interval Matrix Enclosures
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In this talk I described using interval matrix enclosures to characterize the geometry of the space of value functions in reinforcement learning problems, especially POMDPs.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.