Duality between Feature Selection and Data Clustering

The feature-selection problem is formulated from an information-theoretic perspective. We show that the problem can be efficiently solved by an extension of the recently proposed info-clustering paradigm. This reveals the fundamental duality between feature selection and data clustering,which is a consequence of the more general duality between the principal partition and the principal lattice of partitions in combinatorial optimization

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Multi-output regression seeks to infer multiple latent functions using data from multiple groups/sources while accounting for potential between-group similarities. In this paper, we consider multi-output regression under a weakly-supervised setting where a subset of data points from multiple groups are unlabeled. We use dependent Gaussian processes for multiple outputs constructed by convolutions with shared latent processes. We introduce hyperpriors for the multinomial probabilities of the unobserved labels and optimize the hyperparameters which we show improves estimation. We derive two variational bounds: (i) a modified variational bound for fast and stable convergence in model inference, (ii) a scalable variational bound that is amenable to stochastic optimization. We use experiments on synthetic and real-world data to show that the proposed model outperforms state-of-the-art models with more accurate estimation of multiple latent functions and unobserved labels

Regional Influences on Chinese Medicine Education: Comparing Australia and Hong Kong

© 2016 Caragh Brosnan et al. High quality education programs are essential for preparing the next generation of Chinese medicine (CM) practitioners. Currently, training in CM occurs within differing health and education policy contexts. There has been little analysis of the factors influencing the form and status of CM education in different regions. Such a task is important for understanding how CM is evolving internationally and predicting future workforce characteristics. This paper compares the status of CM education in Australia and Hong Kong across a range of dimensions: historical and current positions in the national higher education system, regulatory context and relationship to the health system, and public and professional legitimacy. The analysis highlights the different ways in which CM education is developing in these settings, with Hong Kong providing somewhat greater access to clinical training opportunities for CM students. However, common trends and challenges shape CM education in both regions, including marginalisation from mainstream health professions, a small but established presence in universities, and an emphasis on biomedical research. Three factors stand out as significant for the evolution of CM education in Australia and Hong Kong and may have international implications: continuing biomedical dominance, increased competition between universities, and strengthened links with mainland China

Fast matrix computations for pair-wise and column-wise commute times and Katz scores

We first explore methods for approximating the commute time and Katz score between a pair of nodes. These methods are based on the approach of matrices, moments, and quadrature developed in the numerical linear algebra community. They rely on the Lanczos process and provide upper and lower bounds on an estimate of the pair-wise scores. We also explore methods to approximate the commute times and Katz scores from a node to all other nodes in the graph. Here, our approach for the commute times is based on a variation of the conjugate gradient algorithm, and it provides an estimate of all the diagonals of the inverse of a matrix. Our technique for the Katz scores is based on exploiting an empirical localization property of the Katz matrix. We adopt algorithms used for personalized PageRank computing to these Katz scores and theoretically show that this approach is convergent. We evaluate these methods on 17 real world graphs ranging in size from 1000 to 1,000,000 nodes. Our results show that our pair-wise commute time method and column-wise Katz algorithm both have attractive theoretical properties and empirical performance.Comment: 35 pages, journal version of http://dx.doi.org/10.1007/978-3-642-18009-5_13 which has been submitted for publication. Please see http://www.cs.purdue.edu/homes/dgleich/publications/2011/codes/fast-katz/ for supplemental code

Posttraumatic Stress Among Syrian Refugees: Trauma Exposure Characteristics, Trauma Centrality, and Emotional Suppression

© Washington School of Psychiatry. Objectives: This study revisited the prevalence of posttraumatic stress disorder (PTSD) and examined a hypothesized model describing the interrelationship between trauma exposure characteristics, trauma centrality, emotional suppression, PTSD, and psychiatric comorbidity among Syrian refugees. Methods: A total of 564 Syrian refugees participated in the study and completed the Harvard Trauma Questionnaire, General Health Questionnaire (GHQ-28), Centrality of Event Scale, and Courtauld Emotional Control Scale. Results: Of the participants, 30% met the cutoff for PTSD. Trauma exposure characteristics (experiencing or witnessing horror and murder, kidnapping or disappearance of family members or friends) were associated with trauma centrality, which was associated with emotional suppression. Emotional suppression was associated with PTSD and psychiatric comorbid symptom severities. Suppression mediated the path between trauma centrality and distress outcomes. Conclusions: Almost one-third of refugees can develop PTSD and other psychiatric problems following exposure to traumatic events during war. A traumatized identity can develop, of which life-threatening experiences is a dominant feature, leading to suppression of depression with associated psychological distress