A Data Scientist Plays Games: Nick Berry

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A Data Scientist Plays Games.  This is a presentation broken down into two parts.  The first is how to use mathematical techniques to analyze classic card and board games, and the second part is how data science techniques were applied in real life to support games on the Facebook platform.  This presentation is about 1.5 hours, with a target audience probably suited to CS/software engineering.  It’s light-hearted and fun.

 

This event will be hosted online via Zoom

 

Nick Berry, a native of the UK, has lived in Seattle for the last 25 years. He was educated as a rocket scientist and aircraft designer, graduating with a Masters Degree in Aeronautical and Astronautical Engineering.

Upon graduation, he joined a group of friends to form a software company, specializing in electronic mapping and route planning. This company was grown organically, and earned an unprecedented number of awards and accolades, including the British Design Award and The Queen’s Award for Technology, presented by Her Majesty in 1991. In 1994 Nick was recognized by the Sunday Times Magazine as “One of the top 50 entrepreneurs of the decade”. In 1994, after the company had grown to 50 people worldwide, it was sold to Microsoft.

Nick moved to America with the sale and spent 14 years working for Microsoft, the last ten of which were in the Microsoft Casual Game team. During his tenure, he filed a variety of patents for Microsoft, and represented Microsoft at various conferences and speaking engagements.

After leaving Microsoft, he joined RealNetworks to work as the GM of customer analytics for their games division, GameHouse.

After GameHouse, Nick spent five years as a Data Scientist, working for Facebook in their Seattle office.

In addition to his engineering expertise, Nick is passionate about data privacy and holds a CIPP qualification from the International Association of Privacy Professionals. He is an active member of the privacy community and speaks at various events about the legal and ethical aspects of data collection, use, and destruction.

In July 2013, Nick gave a TEDx talk about Passwords and the Internet, and in 2015 was nominated by GeekWire as Geek-of-the-week. In 2019 he was recognized as one of the 50 over 50 in the video games industry.

UM Biostatistics Seminar: Veronika Rockova, PhD, University of Chicago

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Veronika Rockova, Ph.D.

Assistant Professor in Econometrics and Statistics

The University of Chicago Booth

 

‘Fast Bayesian Factor Analysis via Automatic Rotations to Sparsity’

Abstract: Rotational post hoc transformations have traditionally played a key role in enhancing the interpretability of factor analysis. Regularization methods also serve to achieve this goal by prioritizing sparse loading matrices. In this work, we bridge these two paradigms with a unifying Bayesian framework. Our approach deploys intermediate factor rotations throughout the learning process, greatly enhancing the effectiveness of sparsity inducing priors. These automatic rotations to sparsity are embedded within a PXL-EM algorithm, a Bayesian variant of parameter-expanded EM for posterior mode detection. By iterating between soft-thresholding of small factor loadings and transformations of the factor basis, we obtain (a) dramatic accelerations, (b) robustness against poor initializations, and (c) better oriented sparse solutions. To avoid the prespecification of the factor cardinality, we extend the loading matrix to have infinitely many columns with the Indian buffet process (IBP) prior. The factor dimensionality is learned from the posterior, which is shown to concentrate on sparse matrices. Our deployment of PXL-EM performs a dynamic posterior exploration, outputting a solution path indexed by a sequence of spike-and-slab priors. For accurate recovery of the factor loadings, we deploy the spike-and-slab LASSO prior, a two-component refinement of the Laplace prior. A companion criterion, motivated as an integral lower bound, is provided to effectively select the best recovery. The potential of the proposed procedure is demonstrated on both simulated and real high-dimensional data, which would render posterior simulation impractical. Supplementary materials for this article are available online.

Bio: Veronika Rockova is Assistant Professor in Econometrics and Statistics at the University of Chicago Booth School of Business. Her work brings together statistical methodology, theory and computation to develop high-performance tools for analyzing large datasets. Her research interests reside at the intersection of Bayesian and frequentist statistics, and focus on: data mining, variable selection, optimization, non-parametric methods, factor models, high-dimensional decision theory and inference. She has authored a variety of published works in top statistics journals. In her applied work, she has contributed to the development of risk stratification and prediction models for public reporting in healthcare analytics.

Prior to joining Booth, Rockova held a Postdoctoral Research Associate position at the Department of Statistics of the Wharton School at the University of Pennsylvania. Rockova holds a PhD in biostatistics from Erasmus University (The Netherlands), an MSc in biostatistics from Universiteit Hasselt (Belgium) and both an MSc in mathematical statistics and a BSc in general mathematics from Charles University (Czech Republic).

Besides enjoying statistics, she is a keen piano player.

 

Light refreshments for seminar guests will be served at 3:00 p.m. in 3755.

Advanced Research Computing at Michigan — An Overview

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Brock Palen, Associate Director of Advanced Research Computing – Technology Services, will provide an overview of the resources available to researchers engaged in computationally intensive science on the University of Michigan campus.

The talk is open to researchers from any department at U-M.

The session will address:

  • high performance computing services
  • data science services such as Hadoop and Spark
  • research storage
  • cloud services
  • networking services
  • grant consultation and collaboration
  • access to off-campus resources.

There will be time for questions and answers after the presentation.