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Found 6 papers, 0 papers with code
InfoGram and Admissible Machine Learning
We have entered a new era of machine learning (ML), where the most accurate algorithm with superior predictive power may not even be deployable, unless it is admissible under the regulatory constraints.
On The Problem of Relevance in Statistical Inference
This paper is dedicated to the "50 Years of the Relevance Problem" - a long-neglected topic that begs attention from practical statisticians who are concerned with the problem of drawing inference from large-scale heterogeneous data.
Unified Statistical Theory of Spectral Graph Analysis
The goal of this paper is to show that there exists a simple, yet universal statistical logic of spectral graph analysis by recasting it into a nonparametric function estimation problem.
CDfdr: A Comparison Density Approach to Local False Discovery Rate Estimation
Efron et al. (2001) proposed empirical Bayes formulation of the frequentist Benjamini and Hochbergs False Discovery Rate method (Benjamini and Hochberg, 1995).
Nonlinear Time Series Modeling: A Unified Perspective, Algorithm, and Application
A new comprehensive approach to nonlinear time series analysis and modeling is developed in the present paper.
United Statistical Algorithm, Small and Big Data: Future OF Statistician
This article provides the role of big idea statisticians in future of Big Data Science.
