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Robert Tibshirani

Researcher at Stanford University

Publications -  620
Citations -  359457

Robert Tibshirani is an academic researcher from Stanford University. The author has contributed to research in topics: Lasso (statistics) & Gene expression profiling. The author has an hindex of 147, co-authored 593 publications receiving 326580 citations. Previous affiliations of Robert Tibshirani include University of Toronto & University of California.

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Regularization for supervised learning via the "hubNet" procedure

TL;DR: The hubNet procedure fits a hub-based graphical model to the predictors, to estimate the amount of "connection" that each predictor has with other predictors that yields a set of predictor weights that are then used in a regularized regression such as the lasso or elastic net.
Journal ArticleDOI

Post model‐fitting exploration via a “Next‐Door” analysis

TL;DR: This procedure deletes each chosen predictor and refits the lasso to get a set of models that are “close” to the chosen “base model,” and compares the error rates of the base model with that of nearby models.
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An Open Repository of Real-Time COVID-19 Indicators

TL;DR: The COVIDcast API as mentioned in this paper provides open access to both traditional public health surveillance signals (cases, deaths, and hospitalizations) and many auxiliary indicators of COVID-19 activity, such as signals extracted from de-identified medical claims data, massive online surveys, cell phone mobility data, and internet search trends.
Patent

Methods and compositions for determining risk of treatment toxicity

TL;DR: In this article, an expression profile for the transcriptional response to a therapy is obtained from the patient and compared to a reference profile to determine whether the patient is susceptible to toxicity.