A New Distribution-Random Limit Normal Distribution

This paper introduces a new distribution to improve tail risk modeling. Based on the classical normal distribution, we define a new distribution by a series of heat equations. Then, we use market data to verify our model

Determinants of Job Turnover Intentions: Evidence from Singapore

This paper explores both observable and unobservable variables that would affect employed workers’ decisions on job change. We find that age, job satisfaction, satisfaction with working environment or job security, and firm size are among the major factors determining workers’ intentions of job-to-job mobility. Younger workers and workers in smaller firms are more likely to look for other jobs. We also find that men are more likely to consider a change in job than women, but when “actually looking for another job” is concerned, men and women do not differ. Furthermore, monthly income and working sector contribute significantly to looking for other jobs.Voluntary job-to-job mobility; Job satisfaction; Logistic regression model

Collaborative Filtering with Social Exposure: A Modular Approach to Social Recommendation

This paper is concerned with how to make efficient use of social information to improve recommendations. Most existing social recommender systems assume people share similar preferences with their social friends. Which, however, may not hold true due to various motivations of making online friends and dynamics of online social networks. Inspired by recent causal process based recommendations that first model user exposures towards items and then use these exposures to guide rating prediction, we utilize social information to capture user exposures rather than user preferences. We assume that people get information of products from their online friends and they do not have to share similar preferences, which is less restrictive and seems closer to reality. Under this new assumption, in this paper, we present a novel recommendation approach (named SERec) to integrate social exposure into collaborative filtering. We propose two methods to implement SERec, namely social regularization and social boosting, each with different ways to construct social exposures. Experiments on four real-world datasets demonstrate that our methods outperform the state-of-the-art methods on top-N recommendations. Further study compares the robustness and scalability of the two proposed methods.Comment: Accepted for publication at the 32nd Conference on Artificial Intelligence (AAAI 2018), New Orleans, Louisian

Extended Quark Potential Model from Random Phase Approximation

The quark potential model is extended to include the sea quark excitation using the random phase approximation (RPA). The effective quark interaction preserves the important Quantum Chromodynamics (QCD) properties -- chiral symmetry and confinement simultaneously. A primary qualitive analysis shows that the $\pi$ meson as a well-known typical Goldstone boson and the other mesons made up of valence $q\bar{q}$ quark pair such as the $\rho$ meson can also be described in this extended quark potential model