Tom LaGatta

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Recent research has helped to cultivate growing awareness that machine-learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science community, leaving its members with little concrete guidance to proactively address these concerns. This article(More)
A systems-biology approach to complex disease (such as cancer) is now complementing traditional experience-based approaches, which have typically been invasive and expensive. The rapid progress in biomedical knowledge is enabling the targeting of disease with therapies that are precise, proactive, preventive, and personalized. In this paper, we summarize(More)
We model elections between two parties in a Poisson random population of voters (Myerson 1998, 2000). In addition to offering different policy benefits, parties offer contingent prizes to those identifiable groups of voters that offer the highest level of political support. In large populations, voters are only likely to influence the electoral outcome when(More)
This paper presents a wireframe algorithm that helps visualize embedded Riemannian surfaces in R. Using information provided by the induced metric, also known as the first fundamental form defined in the Euclidean space, the algorithm aims to find an isometric embedding of the intrinsic surface in the three-dimensional space. The fundamental idea is to use(More)
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