Practical Collapsed Stochastic Variational Inference for the HDP

Recent advances have made it feasible to apply the stochastic variational paradigm to a collapsed representation of latent Dirichlet allocation (LDA). While the stochastic variational paradigm has successfully been applied to an uncollapsed representation of the hierarchical Dirichlet process (HDP), no attempts to apply this type of inference in a collapsed setting of non-parametric topic modeling have been put forward so far. In this paper we explore such a collapsed stochastic variational Bayes inference for the HDP. The proposed online algorithm is easy to implement and accounts for the inference of hyper-parameters. First experiments show a promising improvement in predictive performance.Comment: NIPS Workshop; Topic Models: Computation, Application, and Evaluatio

When Politicians Talk: Assessing Online Conversational Practices of Political Parties on Twitter

Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different - mostly qualitative - aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties.Comment: 10 pages, 2 figures, 3 tables, Proc. 8th International AAAI Conference on Weblogs and Social Media (ICWSM 2014

The impact of career counseling plus DISCOVER (Internet version) on the academic achievement of high school sophomores at risk for dropping out of school

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file viewed on (April 25, 2007)Vita.Thesis (Ph.D.) University of Missouri-Columbia 2006.The United States continues to struggle with the problem of high school dropouts. Researchers and educators have identified and developed interventions to address this problem, including prevention programs within the schools to assist with academic and personal struggles, as well as career guidance programs, such as ACT's DISCOVER, designed to strengthen career development. Poor academic achievement has been identified as a main predictor for dropping out. Thus, the main purpose of this study was to evaluate the combined effect on academic achievement of both DISCOVER and career counseling with at-risk sophomores. Data were collected from 33 at-risk high school sophomores. Based on the analyses, there is statistical support that the number of credits earned by the students increased, supporting the use of the combined intervention in positively impacting the academic performance of at risk students. It is recommended that further research with a larger sample size be conducted to further explore these interventions and their impact on academic achievement and preventing high school dropouts.Includes bibliographical reference

Habitat selection of Eurasian woodcock Scolopax rusticola during the spring migration period in Hungary

To establish a decent regulation of the hunting of woodcock in Hungary, a monitoring programme started in 2009 at a national scale. More than 900 participating observers collect data of woodcock during synchronized censuses each spring and in autumn to have basic knowledge of woodcock presence and abundance in the country. Data collecting locations were selected by the observers themselves based on their former experiences, which was primarily influenced by the former knowledge about habitat use of woodcock. Their selection of sites could primarily be influenced by the former knowledge about habitat use of woodcock. This situation offers an opportunity to evaluate this choice of habitats. In this study we investigated the habitat selection of woodcock during spring migration and we tested whether the preceding designation of observation points reflects enough knowledge about their habitat preferences. We used four year spring observation data of the Hungarian woodcock monitoring programme based on synchronized censuses. In order to evaluate the choice of the observers, observation points were buffered with a radius of 874 meters - 2* radius of a 60 ha circle which is known to be used by woodcock individuals in the evening roding period. We intersected the buffers with the Corine Landcover map, and we compared their composition with the composition of buffers of randomly generated points.To evaluate the choice of the birds, correlation between landcover types preferred or avoided by the observers and the detections of woodcock was tested using the nonparametric Spearman correlation. In the case of forests we performed an additional analysis: We classified the buffers using 3 categories of their forest cover rates (0-45% OPEN, 45-77% MID, 77-100% FORESTED). We took 50 random samples of each forest cover rate class per year and we tested the differences among them in the number of woodcock detections and the frequencies of positive sites (where woodcock observation happened).According to our results, the locations of the observation points might not be resulted by random choice. Most landcover types preferred or avoided are also correlated with woodcock abundance. However the correlations we have found were weak. The key element of choice is the presence of forests. The higher rate of broad-leaved forests near the points can raise, the higher rate of discontinuous urban fabric or non-irrigated arable land can lower detection probability

Measuring mitochondria-derived reactive oxygen species in cell culture: Challenges and limitations

Context. Post-processing algorithms play a key role in pushing the detection limits of high-contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI enable the production of science-ready images relying on unsupervised learning techniques, such as low-rank approximations, for generating a model point spread function (PSF) and subtracting the residual starlight and speckle noise. Aims. In order to maximize the detection rate of HCI instruments and survey campaigns, advanced algorithms with higher sensitivities to faint companions are needed, especially for the speckle-dominated innermost region of the images. Methods. We propose a reformulation of the exoplanet detection task (for ADI sequences) that builds on well-established machine learning techniques to take HCI post-processing from an unsupervised to a supervised learning context. In this new framework, we present algorithmic solutions using two different discriminative models: SODIRF (random forests) and SODINN (neural networks). We test these algorithms on real ADI datasets from VLT/NACO and VLT/SPHERE HCI instruments. We then assess their performances by injecting fake companions and using receiver operating characteristic analysis. This is done in comparison with state-of-the-art ADI algorithms, such as ADI principal component analysis (ADI-PCA). Results. This study shows the improved sensitivity versus specificity trade-off of the proposed supervised detection approach. At the diffraction limit, SODINN improves the true positive rate by a factor ranging from ∼2 to ∼10 (depending on the dataset and angular separation) with respect to ADI-PCA when working at the same false-positive level. Conclusions. The proposed supervised detection framework outperforms state-of-the-art techniques in the task of discriminating planet signal from speckles. In addition, it offers the possibility of re-processing existing HCI databases to maximize their scientific return and potentially improve the demographics of directly imaged exoplanets.VORTE