Jerry in the Age of Trees Werner Stuetzle Department of Statistics, - - PowerPoint PPT Presentation

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Jerry in the Age of Trees Werner Stuetzle Department of Statistics, UW May 15, 2019 At a time long long ago The Car The Fashion The Band The Stanford Stat Computing Facility The Frontier Virtually Unlimited Storage The Message Should be

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Jerry in the Age of Trees

Werner Stuetzle

Department of Statistics, UW

May 15, 2019

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At a time long long ago

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The Car

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The Fashion

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The Band

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The Stanford Stat Computing Facility

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The Frontier

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Virtually Unlimited Storage

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The Message Should be Clear

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Who’s this Cool Dude??

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Gems - Not so Hidden

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PRIM-9: An interactive multidimensional data display and analysis system (with Mary Anne Fisherkeller and John

Tukey, 1974, 208 citations)

A Projection Pursuit algorithm for exploratory data analysis (with John Tukey, 1974, 2245 citations)

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An algorithm for finding best matches in logarithmic time (with Jon Bentley and Ari Finkel, 1976, 3150 Citations) Data structures for range searching (with Jon Bentley,

1979, 814 citations)

A recursive partitioning decision rule for nonparametric classification (1977, 507 citations) A tree-structured approach to nonparametric multiple regression (acknowledges Leo Breiman, Charles Stone, Larry

Rafsky, 1979, 67 citations)

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Fast algorithms for constructing minimal spanning trees in coordinate spaces (with Jon Bentley, 1978, 137 citations) Multivariate generalizations of the Wald-Wolfowitz and Smirnov two-sample tests (with Larry Rafsky, 1979, 606

citations)

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Hidden Gems

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A nonparametric procedure for comparing multivariate point sets (with Sam Steppel, 1973, 13 citations)

Given: Two samples S1 and S2. Question: Are they from the same population? Idea: ◮ For each obs i in S1 ∪ S2 count number of S1 obs among its k nearest neighbors ⇒ mi ◮ If they are from the same population then the distribution of mi for obs in S1 and obs in S2 should be the same. ◮ Comparison of univariate distributions can be calibrated using permutations.

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Data analysis techniques for high energy particle physics (1974, 45 citations)

Given: Two sets of features X and Y observed for the same collection of objects. Question: Are they independent? ◮ For each obs i find k nearest neighbors in X-space and k nearest neighbors in Y -space. ◮ Find mi number of shared nearest neighbors ◮ Compare to permutation distribution

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A nested partitioning procedure for numerical multiple integration and adaptive importance sampling (with

Margaret Wright (?), 1978, 51 citations) Goal: Compute integral of multivariate function f over a box. Idea: ◮ There may be small regions that dominate the integral ⇒ need to stratify. ◮ Strata consist of axis parallel boxes ◮ Optimal strata depend on sd of f , but sd is as hard to estimate as mean ◮ Use numerical optimization to find max and min of f in box

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