Split Hamiltonian Monte Carlo

We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting” the Hamiltonian in a way that allows much of the movement around the state space to be done at low computational cost. One context where this is possible is when the log density of the distribution of interest (the potential energy function) can be written as the log of a Gaussian density, which is a quadratic function, plus a slowly-varying function. Hamiltonian dynamics for quadratic energy functions can be analytically solved. With the splitting technique, only the slowly-varying part of the energy needs to be handled numerically, and this can be done with a larger stepsize (and hence fewer steps) than would be necessary with a direct simulation of the dynamics. Another context where splitting helps is when the most important terms of the potential energy function and its gradient can be evaluated quickly, with only a slowly-varying part requiring costly computations. With splitting, the quick portion can be handled with a small stepsize, while the costly portion uses a larger stepsize. We show that both of these splitting approaches can reduce the computational cost of sampling from the posterior distribution for a logistic regression model, using either a Gaussian approximation centered on the posterior mode, or a Hamiltonian split into a term that depends on only a small number of critical cases, and another term that involves the larger number of cases whose influence on the posterior distribution is small.     

基于在线评论数据的产品需求趋势挖掘

随着经济水平的提高和物质生活的丰富，消费者的需求变化也越来越快。能否迎合市场需求的变化是企业产品成功的关键。随着社交媒体的发展，消费者为了分享购物体验发表了许多在线评论信息，其中蕴含着消费者的需求变化。本文在产品特征提取和属性情感分析的基础上，构建了垃圾评论识别模型。然后，利用时间序列分析模型预测下阶段的产品属性关注度和情感计算。最后结合历史数据的变化趋势，分析产品属性的重要性和市场满意情况。利用汽车论坛上的汽车评论数据对本文提出的研究模型进行了验证。研究结果可以为企业制定营销策略以及产品改进与创新提供决策支持。     

Context Matters: Differential Effects of Discrimination by Environmental Context on Depressive Symptoms Among College Students of Color

Clinical Social Work Journal - Experiences with more subtle racism – which have been called microaggressions – have a host of negative effects on health, mental health, educational...     

National Language Capacity in Global Competition

The term national language capacity refers to the sum total of a nation’s ability to grasp linguistic resources, provide language services, deal with linguistic issues, develop the language, and related tasks. Key capacities include the possession of linguistic resources, utilization of language and language services, development and use of linguistic resources, the language of the members of the nation, reserves of linguistic talent, language management, development of language enterprises and linguistic influence. The development of informatization has made national language capacity an important part of national strength. It is hard power as well as soft power, playing a very important role in social progress and cultural inheritance, in promoting economic development and technological innovation, and in protecting a country’s national security and international development.     

人工智能时代的话语悖论与结构转向

以追求智能、精准为核心的技术认知对突发社会问题的预测失灵,形塑了人工智能时代的话语悖论。此悖论体现出盲目崇尚加速的、闭合化的现代性认知结构的困窘,且揭示了晚近技术反思的谱系化与经验"二分"的双重结构观的局限性,进而使超越悖论的结构转向成为必须面对的命题。因此关键在于以突发社会问题为节点,面向日常生活,实现对"二分"的总体性统合。唯有把握日常生活在突发问题中可能产生的反转契机,合理审视智能化的技术,促使技术的精准思维融入于日常生活之中,方能为加速多变的现代科学创设总体化的良善格局。     

基于犹豫模糊信息投影技术的双边匹配决策方法

文章针对犹豫模糊信息下的匹配问题,提出了一种双边匹配决策分析方法.给出了犹豫模糊信息的双边匹配问题描述,将双边主体给出的犹豫模糊信息依据投影法进行信息的集结,构建了两个投影矩阵,依据双方主体组合满意度构建了匹配度矩阵.在此基础上,通过求解双边匹配优化模型,得出双边主体最优匹配结果.最后,以IT外包供需双方的匹配实例说明了所提出方法的可行性和实用性.     

Semi-empirical likelihood inference for the ROC curve with missing data

The receiver operating characteristic (ROC) curve is one of the most commonly used methods to compare the diagnostic performance of two or more laboratory or diagnostic tests. In this paper, we propose semi-empirical likelihood based confidence intervals for ROC curves of two populations, where one population is parametric and the other one is non-parametric and both have missing data. After imputing missing values, we derive the semi-empirical likelihood ratio statistic and the corresponding likelihood equations. It is shown that the log-semi-empirical likelihood ratio statistic is asymptotically scaled chi-squared. The estimating equations are solved simultaneously to obtain the estimated lower and upper bounds of semi-empirical likelihood confidence intervals. We conduct extensive simulation studies to evaluate the finite sample performance of the proposed empirical likelihood confidence intervals with various sample sizes and different missing probabilities.     

景气指标分类方法的理论研究与实证

景气指标分类是景气预测法中至关重要的环节.在以往的文献中,一般采用一种方法对备选指标进行景气分类,但其结果还存在优化的空间.文章采用四种典型的景气指标分类方法:峰谷对应法、时差相关分析法、K-L信息量法、灰色关联度指标分类法对同样的多个指标进行分类.按照初定方案对四种方法的结果进行综合分析,对结果进行优化调整,应用实例表明:四种方法的优化调整结果比单一方法的结果更合理、更有效、更具有科学性.