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Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data
Directional data consist of observations distributed on a (hyper)sphere,...
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Pattern graphs: a graphical approach to nonmonotone missing data
We introduce the concept of pattern graphs–directed acyclic graphs repre...
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Solution manifold and Its Statistical Applications
A solution manifold is the collection of points in a d-dimensional space...
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Polygames: Improved Zero Learning
Since DeepMind's AlphaZero, Zero learning quickly became the state-of-th...
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Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era
The field of astronomy has arrived at a turning point in terms of size a...
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A statistical framework for measuring the temporal stability of human mobility patterns
Despite the growing popularity of human mobility studies that collect GP...
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Nonparametric Pattern-Mixture Models for Inference with Missing Data
Pattern-mixture models provide a transparent approach for handling missi...
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Statistical Inference with Local Optima
We study the statistical properties of an estimator derived by applying ...
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Detecting Galaxy-Filament Alignments in the Sloan Digital Sky Survey III
Previous studies have shown the filamentary structures in the cosmic web...
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Functional Summaries of Persistence Diagrams
One of the primary areas of interest in applied algebraic topology is pe...
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On the use of bootstrap with variational inference: Theory, interpretation, and a two-sample test example
Variational inference is a general approach for approximating complex de...
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A Note on Community Trees in Networks
We introduce the concept of community trees that summarizes topological ...
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Oracle Importance Sampling for Stochastic Simulation Models
We consider the problem of estimating an expected outcome from a stochas...
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Statistical Inference Using Mean Shift Denoising
In this paper, we study how the mean shift algorithm can be used to deno...
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Statistical Inference for Cluster Trees
A cluster tree provides a highly-interpretable summary of a density func...
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Statistical Analysis of Persistence Intensity Functions
Persistence diagrams are two-dimensional plots that summarize the topolo...
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Statistical Inference using the Morse-Smale Complex
The Morse-Smale complex of a function f decomposes the sample space into...
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Optimal Ridge Detection using Coverage Risk
We introduce the concept of coverage risk as an error measure for densit...
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Risk Bounds For Mode Clustering
Density mode clustering is a nonparametric clustering method. The cluste...
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Nonparametric modal regression
Modal regression estimates the local modes of the distribution of Y give...
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