AutoEncoder Inspired Unsupervised Feature Selection

High-dimensional data in many areas such as computer vision and machine learning tasks brings in computational and analytical difficulty. Feature selection which selects a subset from observed features is a widely used approach for improving performance and effectiveness of machine learning models with high-dimensional data. In this paper, we propose a novel AutoEncoder Feature Selector (AEFS) for unsupervised feature selection which combines autoencoder regression and group lasso tasks. Compared to traditional feature selection methods, AEFS can select the most important features by excavating both linear and nonlinear information among features, which is more flexible than the conventional self-representation method for unsupervised feature selection with only linear assumptions. Experimental results on benchmark dataset show that the proposed method is superior to the state-of-the-art method.Comment: accepted by ICASSP 201

QCD Radiative Correction to the Hadronic Annihilation Rate of 1+−1^{+-} Heavy Quarkonium

Hadronic annihilation rate of $1^{+-}$ heavy quarkonium is given to next-to-leading order in $\alpha_s$ and leading order in $v^2$ using a recently developed factorization formalism which is based on NRQCD. The result includes both the annihilation of P-wave color-singlet $Q\bar{Q}$ component, and the annihilation of S-wave color-octet $Q\bar{Q}$ component of the quarkonium. The notorious infrared divergences due to soft gluons, i.e., the Logarithms associated with the binding energy, encountered in previous perturbative calculations of $1^{+-}$ quarkonium decays are found to be explicitly cancelled, and a finite result for the decay width to order $\alpha_s^3$ is then obtained.Comment: 15 pages latex (6 figures included). In this revised version a update reference and acknowledgement are include

The Use of English Transition Markers in Chinese and British University Student Writing

Chinese students are the largest group of overseas students in the UK (Leedham 2015), so various studies have been conducted to compare their academic writing with native English speakers’. Metadiscourse resources are very important devices to show how the writer responds to his or her potential readers (Hyland 2005; Ädel 2006), but little research has been carried out to examine how Chinese and English student writers employ them in detail in their assignments. Furthermore, fewer studies have been carried out to compare the writing of the two groups of students with highly-matched texts. The present study was carried out to investigate Chinese and English student writing using a highly-matched corpus in terms of level, discipline, and genre family. It aimed to identify transitions and the use of transitions in student academic writing. The findings show similarities in the writing of the Chinese and English students. They both tended to use transitions more frequently in non-science disciplines (e.g. Law and Linguistics) and discursive genre families (e.g. Critique and Essay), while they both tended to employ less frequently in science disciplines (e.g. Food Science and Biology) and in technical genre families (e.g. Methodology Recount and Design Specification). Since English students are native English speakers and they may have greater prior exposure to academic writing, their writing reflects better understanding of the transition items in terms of meaning and formality. On the other hand, since Chinese students are non-native English speakers, they have more English grammar courses before their undergraduate education. As a result, the use of punctuation with transitions is more accurate in their writing. Furthermore, English students appear to be more sophisticated in their use of co-occurring transitions (e.g. and thus, but nevertheless). This has not been previously revealed in the literature. Both groups of students make both appropriate and inappropriate use of transitions which are worthy of note

Development of a Personalized Quantitative Faculty Annual Evaluation System

Faculty annual evaluation is critical for faculty career development and department success. Our department developed a quantitative faculty evaluation metrics system that is more objective, consistent, flexible, personalized, transparent, and dynamic scoring system. We have implemented the system for 2 years and the outcomes are very encouraging in promoting faculty and department success.Cockrell School of Engineerin