A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of th...

Mycoplasma gallisepticum (MG) is a major and economically significant pathogen of avian species. When administered before lay, F-strain MG (FMG) can reduce egg production during lay, but the ts-11 strain of MG (ts11MG) does not exert this effect. Two trials were conducted to determine the effects of pre-lay vaccinations of ts11MG, MG-Bacterin (MGBac), or their combination, in conjunction with a...

Most state-of-the-art statistical machine translation systems use log-linear models, which are defined in terms of hypothesis features and weights for those features. It is standard to tune the feature weights in order to maximize a translation quality metric, using held-out test sentences and their corresponding reference translations. However, obtaining reference translations is expensive. In...

This short survey discusses the role of regularization in current deep learning research. Up till now, dropout remains the most popular choice of all deep neural network regularization techniques, and is what this survey is centered around. We first give a general introduction and interpretation of dropout (Section 1), followed by some follow-up works which either improve speed or offer analysi...

We present an extension of two policy-iteration based algorithms on weighted graphs (viz., Markov Decision Problems and Max-Plus Algebras). This extension allows us to solve the following inverse problem: considering the weights of the graph to be unknown constants or parameters, we suppose that a reference instantiation of those weights is given, and we aim at computing a constraint on the par...

Background and Objectives: Evaluating the performance of clinical units is critical for effective management of health settings. Certain assessment of clinical variables for performance analysis is not always possible, calling for use of uncertainty theory. This study aimed to develop and evaluate an integrated independent component analysis-fuzzy-data envelopment analysis approach to accurate ...

This paper examines the estimation of global term weights (such as IDF) in information retrieval scenarios where a global view on the collection is not available. In particular, the two options of either sampling documents or of using a reference corpus independent of the retrieval collection are compared using standard IR test collections. In addition, the possibility of pruning term lists bas...