A pooling space is defined to be a ranked partially ordered set with atomic intervals. We show how to construct non-adaptive pooling designs from a pooling space. Our pooling designs are e-error detecting for some e; moreover e can be chosen to be very large compared with the maximal number of defective items. Eight new classes of nonadaptive pooling designs are given, which are related to the ...

Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the...

MOTIVATION If there is insufficient RNA from the tissues under investigation from one organism, then it is common practice to pool RNA. An important question is to determine whether pooling introduces biases, which can lead to inaccurate results. In this article, we describe two biases related to pooling, from a theoretical as well as a practical point of view. RESULTS We model and quantify t...

Genome-wide assocation studies have often been carried out by meta-analysis rather than by pooling individual-level data. For one-dimensional parameter estimates and the corresponding tests of association these meta-analyses lead to essentially no loss of information relative to pooling individual data. The situation is different for multiparameter tests, such as the omnidirectional rare-varian...

BACKGROUND Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin's Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels significantly contributes to the model, different methods are available. For example pooling chi-...

This paper proposes several statistical tests for finite state Markov games to examine the null hypothesis that data from distinct markets can be pooled. We formulate tests of (i) the conditional choice and state transition probabilities, (ii) the steady-state distribution, and (iii) the conditional state distribution given an initial state. If the null cannot be rejected, then the data across ...

Convolutional Neural Network (CNN) is a biologically inspired trainable architecture that can learn invariant features for a number of applications. In general, CNNs consist of alternating convolutional layers, non-linearity layers and feature pooling layers. In this work, a novel feature pooling method, named as mixed pooling, is proposed to regularize CNNs, which replaces the deterministic po...

In recent years, designing the coding and pooling structures in layered networks has been shown to be a useful method for learning high-level feature representations for visual data. Yet, such learning structures have not been extensively studied for audio signals. In this paper, we investigate different pooling strategies based on the sparse coding scheme and propose a temporal pyramid pooling...

Pooling is one of the key elements in a convolutional neural network. It reduces feature map size, thereby enabling training with limited amount computation. The most common pooling methods are average pooling, max and stride pooling. methods, however, have disadvantage that they can perform only specified fixed functions thus expressive power. In this paper, we propose new method named univers...