Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning

The development of cluster computing frameworks has allowed practitioners to scale out various statistical estimation and machine learning algorithms with minimal programming effort. This is especially true for machine learning problems whose objective function is nicely separable across individual data points, such as classification and regression. In contrast, statistical learning tasks involving pairs (or more generally tuples) of data points - such as metric learning, clustering or ranking do not lend themselves as easily to data-parallelism and in-memory computing. In this paper, we investigate how to balance between statistical performance and computational efficiency in such distributed tuplewise statistical problems. We first propose a simple strategy based on occasionally repartitioning data across workers between parallel computation stages, where the number of repartitioning steps rules the trade-off between accuracy and runtime. We then present some theoretical results highlighting the benefits brought by the proposed method in terms of variance reduction, and extend our results to design distributed stochastic gradient descent algorithms for tuplewise empirical risk minimization. Our results are supported by numerical experiments in pairwise statistical estimation and learning on synthetic and real-world datasets.Comment: 23 pages, 6 figures, ECML 201

A statistical network analysis of the HIV/AIDS epidemics in Cuba

The Cuban contact-tracing detection system set up in 1986 allowed the reconstruction and analysis of the sexual network underlying the epidemic (5,389 vertices and 4,073 edges, giant component of 2,386 nodes and 3,168 edges), shedding light onto the spread of HIV and the role of contact-tracing. Clustering based on modularity optimization provides a better visualization and understanding of the network, in combination with the study of covariates. The graph has a globally low but heterogeneous density, with clusters of high intraconnectivity but low interconnectivity. Though descriptive, our results pave the way for incorporating structure when studying stochastic SIR epidemics spreading on social networks

The HIV/AIDS epidemic in Cuba: description and tentative explanation of its low HIV prevalence

<p>Abstract</p> <p>Background</p> <p>The Cuban HIV/AIDS epidemic has the lowest prevalence rate of the Caribbean region. The objective of this paper is to give an overview of the HIV/AIDS epidemic in Cuba and to explore the reasons for this low prevalence.</p> <p>Methods</p> <p>Data were obtained from the Cuban HIV/AIDS programme established in 1983. This programme has an extensive adult HIV testing policy, including testing of all pregnant women. HIV and AIDS cases have been recorded since 1986. Persons found to be HIV-positive are interviewed on their sexual behaviour and partners. Tracing and voluntary testing of these partners are organised. Epidemiological description of this epidemic was obtained from analysis of this data set. Using elementary mathematical analyses, we estimated the coverage of the detection system (percentage of HIV-positive adults detected) and the average period between HIV infection and detection. Estimated HIV prevalence rates were corrected to account for the coverage.</p> <p>Results</p> <p>HIV prevalence has increased since 1996. In 2005, the prevalence among pregnant women was 1.2 per 10,000 (16/137000). Estimated HIV prevalence among 15- to 49-year-olds was 8.1 per 10,000 (4913/6065000; 95%CI: 7.9 per 10,000 – 8.3 per 10,000). Most (77%) of the HIV-positive adults were men, most (85.1%) of the detected HIV-positive men were reported as having sex with men (MSM), and most of the HIV-positive women reported having had sex with MSM. The average period between HIV infection and detection was estimated to be 2.1 years (IQR = 1.7 – 2.2 years). We estimated that, for the year 2005, 79.6% (IQR: 77.3 – 81.4%) of the HIV-positive persons were detected.</p> <p>Conclusion</p> <p>MSM drive the HIV epidemic in Cuba. The extensive HIV testing policy may be an important factor in explaining the low HIV prevalence. To reduce the HIV epidemic in Cuba, the epidemic among MSM should be addressed. To understand this epidemic further, data on sexual behaviour should be collected. Now that antiretroviral therapy is more widely available, the Cuban policy, based on intensive HIV testing and tracing of partners, may be considered as a possible policy to control HIV/AIDS epidemics in other countries.</p

Ageing, Muscle Power and Physical Function: A Systematic Review and Implications for Pragmatic Training Interventions.

BACKGROUND: The physiological impairments most strongly associated with functional performance in older people are logically the most efficient therapeutic targets for exercise training interventions aimed at improving function and maintaining independence in later life. OBJECTIVES: The objectives of this review were to (1) systematically review the relationship between muscle power and functional performance in older people; (2) systematically review the effect of power training (PT) interventions on functional performance in older people; and (3) identify components of successful PT interventions relevant to pragmatic trials by scoping the literature. METHODS: Our approach involved three stages. First, we systematically reviewed evidence on the relationship between muscle power, muscle strength and functional performance and, second, we systematically reviewed PT intervention studies that included both muscle power and at least one index of functional performance as outcome measures. Finally, taking a strong pragmatic perspective, we conducted a scoping review of the PT evidence to identify the successful components of training interventions needed to provide a minimally effective training dose to improve physical function. RESULTS: Evidence from 44 studies revealed a positive association between muscle power and indices of physical function, and that muscle power is a marginally superior predictor of functional performance than muscle strength. Nine studies revealed maximal angular velocity of movement, an important component of muscle power, to be positively associated with functional performance and a better predictor of functional performance than muscle strength. We identified 31 PT studies, characterised by small sample sizes and incomplete reporting of interventions, resulting in less than one-in-five studies judged as having a low risk of bias. Thirteen studies compared traditional resistance training with PT, with ten studies reporting the superiority of PT for either muscle power or functional performance. Further studies demonstrated the efficacy of various methods of resistance and functional task PT on muscle power and functional performance, including low-load PT and low-volume interventions. CONCLUSIONS: Maximal intended movement velocity, low training load, simple training methods, low-volume training and low-frequency training were revealed as components offering potential for the development of a pragmatic intervention. Additionally, the research area is dominated by short-term interventions producing short-term gains with little consideration of the long-term maintenance of functional performance. We believe the area would benefit from larger and higher-quality studies and consideration of optimal long-term strategies to develop and maintain muscle power and physical function over years rather than weeks

Mapping and linking supply- and demand-side measures in climate-smart agriculture. A review

Climate change and food security are two of humanity’s greatest challenges and are highly interlinked. On the one hand, climate change puts pressure on food security. On the other hand, farming significantly contributes to anthropogenic greenhouse gas emissions. This calls for climate-smart agriculture—agriculture that helps to mitigate and adapt to climate change. Climate-smart agriculture measures are diverse and include emission reductions, sink enhancements, and fossil fuel offsets for mitigation. Adaptation measures include technological advancements, adaptive farming practices, and financial management. Here, we review the potentials and trade-offs of climate-smart agricultural measures by producers and consumers. Our two main findings are as follows: (1) The benefits of measures are often site-dependent and differ according to agricultural practices (e.g., fertilizer use), environmental conditions (e.g., carbon sequestration potential), or the production and consumption of specific products (e.g., rice and meat). (2) Climate-smart agricultural measures on the supply side are likely to be insufficient or ineffective if not accompanied by changes in consumer behavior, as climate-smart agriculture will affect the supply of agricultural commodities and require changes on the demand side in response. Such linkages between demand and supply require simultaneous policy and market incentives. It, therefore, requires interdisciplinary cooperation to meet the twin challenge of climate change and food security. The link to consumer behavior is often neglected in research but regarded as an essential component of climate-smart agriculture. We argue for not solely focusing research and implementation on one-sided measures but designing good, site-specific combinations of both demand- and supply-side measures to use the potential of agriculture more effectively to mitigate and adapt to climate change