Institution
University of Chicago
Education•Chicago, Illinois, United States•
About: University of Chicago is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 66716 authors who have published 160098 publications receiving 9644339 citations. The organization is also known as: Chicago University & U of C.
Topics: Population, Cancer, Galaxy, Gene, Transplantation
Papers published on a yearly basis
Papers
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TL;DR: A signaling pathway initiated by eIF2alpha phosphorylation protects cells against metabolic consequences of ER oxidation by promoting the linked processes of amino acid sufficiency and resistance to oxidative stress.
2,920 citations
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23 Jun 2008
TL;DR: A discriminatively trained, multiscale, deformable part model for object detection, which achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge and outperforms the best results in the 2007 challenge in ten out of twenty categories.
Abstract: This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge in ten out of twenty categories. The system relies heavily on deformable parts. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL challenge. Our system also relies heavily on new methods for discriminative training. We combine a margin-sensitive approach for data mining hard negative examples with a formalism we call latent SVM. A latent SVM, like a hidden CRF, leads to a non-convex training problem. However, a latent SVM is semi-convex and the training problem becomes convex once latent information is specified for the positive examples. We believe that our training methods will eventually make possible the effective use of more latent information such as hierarchical (grammar) models and models involving latent three dimensional pose.
2,893 citations
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TL;DR: The authors study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers and find that white names receive 50 percent more callbacks for interviews than African-Americans.
Abstract: We study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-American- or White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to still be prominent in the U.S. labor market. (JEL J71, J64).
2,890 citations
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TL;DR: In this article, the observed market model and associated ordinary least squares estimators are developed in detail, and computationally convenient, consistent estimators for parameters of the market model are calculated and then applied to daily returns of securities listed in the NYSE and ASE.
2,859 citations
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01 Sep 2014
TL;DR: XSEDE's integrated, comprehensive suite of advanced digital services federates with other high-end facilities and with campus-based resources, serving as the foundation for a national e-science infrastructure ecosystem.
Abstract: Computing in science and engineering is now ubiquitous: digital technologies underpin, accelerate, and enable new, even transformational, research in all domains. Access to an array of integrated and well-supported high-end digital services is critical for the advancement of knowledge. Driven by community needs, the Extreme Science and Engineering Discovery Environment (XSEDE) project substantially enhances the productivity of a growing community of scholars, researchers, and engineers (collectively referred to as "scientists"' throughout this article) through access to advanced digital services that support open research. XSEDE's integrated, comprehensive suite of advanced digital services federates with other high-end facilities and with campus-based resources, serving as the foundation for a national e-science infrastructure ecosystem. XSEDE's e-science infrastructure has tremendous potential for enabling new advancements in research and education. XSEDE's vision is a world of digitally enabled scholars, researchers, and engineers participating in multidisciplinary collaborations to tackle society's grand challenges.
2,856 citations
Authors
Showing all 67909 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Solomon H. Snyder | 232 | 1222 | 200444 |
Eugene Braunwald | 230 | 1711 | 264576 |
Kari Stefansson | 206 | 794 | 174819 |
Hagop M. Kantarjian | 204 | 3708 | 210208 |
David Miller | 203 | 2573 | 204840 |
Martin White | 196 | 2038 | 232387 |
Craig B. Thompson | 195 | 557 | 173172 |
Robert C. Nichol | 187 | 851 | 162994 |
Jing Wang | 184 | 4046 | 202769 |
Patrick O. Brown | 183 | 755 | 200985 |
Yusuke Nakamura | 179 | 2076 | 160313 |
H. S. Chen | 179 | 2401 | 178529 |
Joseph Biederman | 179 | 1012 | 117440 |
Daniel J. Eisenstein | 179 | 672 | 151720 |