Boosting Freund Schapire Schapire Singer is one of the most important recent developments in classi cation method ology The performance of many classi cation algorithms often can be dramatically improved by sequentially applying them to reweighted versions of the input data and taking a weighted majority vote of the sequence of classi ers thereby produced We show that this seemingly mysterious ...

Many modern genomic data analysis require implementing regressions where the number of parameters (p, e.g., the number of marker effects) exceeds sample size (n). Implementing these large-p-with-small-n regressions poses several statistical and computational challenges, some of which can be confronted using Bayesian methods. This approach allows integrating various parametric and non-parametric...

Logic regression has been recognized as a tool that can identify and model non-additive genetic interactions using Boolean logic groups. Logic regression, TASSEL-GLM and SAS-GLM were compared for analytical precision using a previously characterized model system to identify the best genetic model explaining epistatic interaction of vernalization-sensitivity in barley. A genetic model containing...

A s t a t i s t i c a l database serves two ma jo r purposes : to p r o v i d e the s t a t i s t i c i a n w i t h a c c u r a t e aggrega te s t a t i s t i c a l i n f o r m a t i o n , and to p r o t e c t the c o n f i d e n t i a l i t y of i n d i v i d u a l database r e c o r d s . A t e c h n i q u e is p resen ted which u t i l i z e s r e g r e s s i o n methodo logy to compromise c...

Multivariate statistical analysis is an important data analysis technique that has found applications in various areas. In this paper, we study some multivariate statistical analysis methods in Secure 2-party Computation (S2C) framework illustrated by the following scenario: two parties, each having a secret data set, want to conduct the statistical analysis on their joint data, but neither par...

Inductive logic programming (ILP) techniques are useful for analyzing data in multi-table relational databases. Learned rules can potentially discover relationships that are not obvious in "flattened" data. Statistical learners, on the other hand, are generally not constructed to search relational data; they expect to be presented with a single table containing a set of feature candidates. Howe...

• Note for i.i.d. samples (xi, yi) ∈ R × R, i = 1, . . . , n, we can always write yi = f0(xi) + i, i = 1, . . . , n, where i, i = 1, . . . , n are i.i.d. random errors, with mean zero. Therefore we can think about the sampling distribution as follows: (xi, i), i = 1, . . . , n are i.i.d. draws from some common joint distribution, where E( i) = 0, and yi, i = 1, . . . , n are generated from the ...

We address the statistical and optimization impacts of using classical sketch versus Hessian sketch to solve approximately the Matrix Ridge Regression (MRR) problem. Prior research has considered the effects of classical sketch on least squares regression (LSR), a strictly simpler problem. We establish that classical sketch has a similar effect upon the optimization properties of MRR as it does...

This paper presents a new method for statistical modelling of prosody control in speech synthesis. The proposed method, which is referred to as Constrained Tree Regression (CTR), can make suitable representation of complex effects of control factors for prosody with a moderate amount of learning data. It is based on recursive splits of predictor variable spaces and partial imposition of constra...

Beef cattle research commonly uses Yield grade (YG) and Quality grade (QG) as outcomes in nutrition and health experiments. These outcomes, as commonly reported and analyzed, are ordinal variables with an assumed rank derived from an underlying latent variable that may or may not be available for analysis. The objective of this study was to employ mixed-effects ordinal regression and approaches...