Institution
University of Minnesota
Education•Minneapolis, Minnesota, United States•
About: University of Minnesota is a education organization based out in Minneapolis, Minnesota, United States. It is known for research contribution in the topics: Population & Transplantation. The organization has 117432 authors who have published 257986 publications receiving 11944239 citations. The organization is also known as: University of Minnesota, Twin Cities & University of Minnesota-Twin Cities.
Topics: Population, Transplantation, Poison control, Health care, Cancer
Papers published on a yearly basis
Papers
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TL;DR: The material covered includes tensor rank and rank decomposition; basic tensor factorization models and their relationships and properties; broad coverage of algorithms ranging from alternating optimization to stochastic gradient; statistical performance analysis; and applications ranging from source separation to collaborative filtering, mixture and topic modeling, classification, and multilinear subspace learning.
Abstract: Tensors or multiway arrays are functions of three or more indices $(i,j,k,\ldots)$ —similar to matrices (two-way arrays), which are functions of two indices $(r,c)$ for (row, column). Tensors have a rich history, stretching over almost a century, and touching upon numerous disciplines; but they have only recently become ubiquitous in signal and data analytics at the confluence of signal processing, statistics, data mining, and machine learning. This overview article aims to provide a good starting point for researchers and practitioners interested in learning about and working with tensors. As such, it focuses on fundamentals and motivation (using various application examples), aiming to strike an appropriate balance of breadth and depth that will enable someone having taken first graduate courses in matrix algebra and probability to get started doing research and/or developing tensor algorithms and software. Some background in applied optimization is useful but not strictly required. The material covered includes tensor rank and rank decomposition; basic tensor factorization models and their relationships and properties (including fairly good coverage of identifiability); broad coverage of algorithms ranging from alternating optimization to stochastic gradient; statistical performance analysis; and applications ranging from source separation to collaborative filtering, mixture and topic modeling, classification, and multilinear subspace learning.
1,284 citations
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Health Canada1, United States Environmental Protection Agency2, Brigham Young University3, University of Texas at Austin4, University of British Columbia5, Health Effects Institute6, McGill University7, University of Minnesota8, Harvard University9, Utrecht University10, University of Washington11, Fudan University12, New York University13, University of California, Los Angeles14, University of Ottawa15, American Cancer Society16, University of California, Davis17, Cancer Prevention Institute of California18, University of New Brunswick19, Dalhousie University20, Carleton University21, Statistics Canada22, University of Toronto23, Chinese Center for Disease Control and Prevention24, St George's, University of London25, University of Hong Kong26, University of Ulm27, SERC Reliability Corporation28
TL;DR: PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
Abstract: Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
1,283 citations
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TL;DR: In this paper, the authors extend existing theories by linking transformational leadership to self-concordance at work, and find that leader behaviors were associated with follower behaviors in two studies using diverse samples and methods.
Abstract: We extend existing theories by linking transformational leadership to “self-concordance” at work. In two studies using diverse samples and methods, leader behaviors were associated with follower te...
1,283 citations
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TL;DR: The Circumplex Model as mentioned in this paper focuses on the three central dimensions of marital and family systems: cohesion, flexibility and communication, and it has been shown that balanced couple and family system tend to be more functional compared to unbalanced systems.
Abstract: The Circumplex Model focuses on the three central dimensions of marital and family systems: cohesion, flexibility and communication. The major hypothesis of the Circumplex Model is that balanced couple and family systems tend to be more functional compared to unbalanced systems. In over 250 studies using the Family Adaptability and Cohesion Scales (FACES), a linear self-report measure, strong support has been found for this hypothesis. In several studies using the Clinical Rating Scale (CRS), a curvilinear observational measure, the hypothesis was also supported. These two assessment tools, the FACES and the CRS, are designed for research, clinical assessment and treatment planning with couples and families.
1,282 citations
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TL;DR: A review of the physical characteristics of sulfur-containing aerosols, with respect to size distribution of physical distributions, sulfur distributions, distribution modal characteristics, nuclei formation rates, aerosol growth characteristics, and in situ measurement, has been made as mentioned in this paper.
1,278 citations
Authors
Showing all 118112 results
Name | H-index | Papers | Citations |
---|---|---|---|
Walter C. Willett | 334 | 2399 | 413322 |
David J. Hunter | 213 | 1836 | 207050 |
David Miller | 203 | 2573 | 204840 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Dennis W. Dickson | 191 | 1243 | 148488 |
David H. Weinberg | 183 | 700 | 171424 |
Eric Boerwinkle | 183 | 1321 | 170971 |
John C. Morris | 183 | 1441 | 168413 |
Aaron R. Folsom | 181 | 1118 | 134044 |
H. S. Chen | 179 | 2401 | 178529 |
Jie Zhang | 178 | 4857 | 221720 |
Jasvinder A. Singh | 176 | 2382 | 223370 |
Feng Zhang | 172 | 1278 | 181865 |
Gang Chen | 167 | 3372 | 149819 |
Hongfang Liu | 166 | 2356 | 156290 |