Distributional semantics and machine learning for statistical machine translation

[EU]Lan honetan semantika distribuzionalaren eta ikasketa automatikoaren erabilera aztertzen dugu itzulpen automatiko estatistikoa hobetzeko. Bide horretan, erregresio logistikoan oinarritutako ikasketa automatikoko eredu bat proposatzen dugu hitz-segiden itzulpen- probabilitatea modu dinamikoan modelatzeko. Proposatutako eredua itzulpen automatiko estatistikoko ohiko itzulpen-probabilitateen orokortze bat dela frogatzen dugu, eta testuinguruko nahiz semantika distribuzionaleko informazioa barneratzeko baliatu ezaugarri lexiko, hitz-cluster eta hitzen errepresentazio bektorialen bidez. Horretaz gain, semantika distribuzionaleko ezagutza itzulpen automatiko estatistikoan txertatzeko beste hurbilpen bat lantzen dugu: hitzen errepresentazio bektorial elebidunak erabiltzea hitz-segiden itzulpenen antzekotasuna modelatzeko. Gure esperimentuek proposatutako ereduen baliagarritasuna erakusten dute, emaitza itxaropentsuak eskuratuz oinarrizko sistema sendo baten gainean. Era berean, gure lanak ekarpen garrantzitsuak egiten ditu errepresentazio bektorialen mapaketa elebidunei eta hitzen errepresentazio bektorialetan oinarritutako hitz-segiden antzekotasun neurriei dagokienean, itzulpen automatikoaz haratago balio propio bat dutenak semantika distribuzionalaren arloan.

Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods

Using mixed logit models to analyse choice data is common but requires ex ante specification of the functional forms of preference distributions. We make the case for greater use of bounded functional forms and propose the use of the Marginal Likelihood, calculated using Bayesian techniques, as a single measure of model performance across non nested mixed logit specifications. Using this measure leads to very different rankings of model specifications compared to alternative rule of thumb measures. The approach is illustrated using data from a choice experiment regarding GM food types which provides insights regarding the recent WTO dispute between the EU and the US, Canada and Argentina and whether labelling and trade regimes should be based on the production process or product composition.

Are large-scale distributional shifts of the blue-winged macaw (Primolius maracana) related to climate change?

Aim To evaluate whether observed geographical shifts in the distribution of the blue-winged macaw (Primolius maracana) are related to ongoing processes of global climate change. This species is vulnerable to extinction and has shown striking range retractions in recent decades, withdrawing broadly from southern portions of its historical distribution. Its range reduction has generally been attributed to the effects of habitat loss; however, as this species has also disappeared from large forested areas, consideration of other factors that may act in concert is merited.Location Historical distribution of the blue-winged macaw in Brazil, eastern Paraguay and northern Argentina.Methods We used a correlative approach to test a hypothesis of causation of observed shifts by reduction of habitable areas mediated by climate change. We developed models of the ecological niche requirements of the blue-winged macaw, based on point-occurrence data and climate scenarios for pre-1950 and post-1950 periods, and tested model predictivity for anticipating geographical distributions within time periods. Then we projected each model to the other time period and compared distributions predicted under both climate scenarios to assess shifts of habitable areas across decades and to evaluate an explanation for observed range retractions.Results Differences between predicted distributions of the blue-winged macaw over the twentieth century were, in general, minor and no change in suitability of landscapes was predicted across large areas of the species' original range in different time periods. No tendency towards range retraction in the south was predicted, rather conditions in the southern part of the species' range tended to show improvement for the species.Main conclusions Our test permitted elimination of climate change as a likely explanation for the observed shifts in the distribution of the blue-winged macaw, and points rather to other causal explanations (e.g. changing regional land use, emerging diseases).

Distributional potential of the Triatoma brasiliensis species complex at present and under scenarios of future climate conditions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

Income Distributional Effects of Decoupled Payments Single Payment Scheme in the European Union. Factor Markets Working Paper No. 29, July 2012

This paper analyses the effects of the Single Payment Scheme (SPS) with and without farm structural change, and focuses on how income distributional effects and farm restructuring are impacted by the SPS under: alternative entitlement tradability, cross-compliance and CAP 'greening' requirements, different SPS implementation models, the entitlement stock, market imperfections and institutional regulations. The authors find that the SPS implication details are highly significant, since farmers’ benefits can range from 100% of the SPS value to a negative policy incidence, and farm structural change may also be hindered by the SPS.

Testing Independence in High Dimensions & Identifiability of Graphical Models

Thesis (Ph.D.)--University of Washington, 2016-06

On the effect of word frequency on distributional similarity

The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.

A distributional analysis of the gender wage gap in Bangladesh

This article empirically investigates the gender wage gap in Bangladesh during the period 2005–2009. Applying unconditional quantile regression models, the article demonstrates that women are paid less than men throughout the wage distribution and the gap is higher at the lower end of the distribution. Discrimination against women is the primary determinant of the wage gap. The article also demonstrates that the observed gender wage gap is likely to be underestimated if we ignore selection in full-time employment. A number of policy implications are discussed.