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Institution

Carnegie Mellon University

EducationPittsburgh, Pennsylvania, United States
About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.


Papers
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Journal ArticleDOI
TL;DR: In this article, the cosmological evolution of the hard X-ray luminosity function (HXLF) of active galactic nuclei (AGNs) in the 2-10 keV luminosity range of 1041.5-1046.5 ergs s-1 was investigated.
Abstract: We investigate the cosmological evolution of the hard X-ray luminosity function (HXLF) of active galactic nuclei (AGNs) in the 2-10 keV luminosity range of 1041.5-1046.5 ergs s-1 as a function of redshift up to 3. From a combination of surveys conducted at photon energies above 2 keV with HEAO 1, ASCA, and Chandra, we construct a highly complete (>96%) sample consisting of 247 AGNs over the wide flux range of 10-10 to 3.8 × 10-15 ergs cm-2 s-1 (2-10 keV). For our purpose, we develop an extensive method of calculating the intrinsic (before absorption) HXLF and the absorption (NH) function. This utilizes the maximum likelihood method, fully correcting for observational biases with consideration of the X-ray spectrum of each source. We find that (1) the fraction of X-ray absorbed AGNs decreases with the intrinsic luminosity and (2) the evolution of the HXLF of all AGNs (including both type I and type II AGNs) is best described with a luminosity-dependent density evolution (LDDE) where the cutoff redshift increases with the luminosity. Our results directly constrain the evolution of AGNs that produce a major part of the hard X-ray background, thus solving its origin quantitatively. A combination of the HXLF and the NH function enables us to construct a purely observation-based population synthesis model. We present basic consequences of this model and discuss the contribution of Compton-thick AGNs to the rest of the hard X-ray background.

1,216 citations

Posted Content
TL;DR: This paper proposes the angular softmax (A-Softmax) loss that enables convolutional neural networks (CNNs) to learn angularly discriminative features in deep face recognition (FR) problem under open-set protocol.
Abstract: This paper addresses deep face recognition (FR) problem under open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen metric space. However, few existing algorithms can effectively achieve this criterion. To this end, we propose the angular softmax (A-Softmax) loss that enables convolutional neural networks (CNNs) to learn angularly discriminative features. Geometrically, A-Softmax loss can be viewed as imposing discriminative constraints on a hypersphere manifold, which intrinsically matches the prior that faces also lie on a manifold. Moreover, the size of angular margin can be quantitatively adjusted by a parameter $m$. We further derive specific $m$ to approximate the ideal feature criterion. Extensive analysis and experiments on Labeled Face in the Wild (LFW), Youtube Faces (YTF) and MegaFace Challenge show the superiority of A-Softmax loss in FR tasks. The code has also been made publicly available.

1,215 citations

Journal ArticleDOI
TL;DR: The time evolution strongly suggests that neglected oxidation of numerous "intermediate volatility" vapors (IVOCs, with saturation concentrations above approximately 1 mg m(-3)) may contribute significantly to ambient SOA formation.
Abstract: A unified framework of semi-volatile partitioning permits models to efficiently treat both semi-volatile primary emissions and secondary organic aerosol production (SOA), and then to treat the chemical evolution (aging) of the aggregate distribution of semi-volatile material. This framework also reveals critical deficiencies in current emissions and SOA formation measurements. The key feature of this treatment is a uniform basis set of saturation vapor pressures spanning the range of ambient organic saturation concentrations, from effectively nonvolatile material at 0.01 microg m(-3) to vapor-phase effluents at 100 mg m(-3). Chemical evolution can be treated by a transformation matrix coupling the various basis vectors. Using this framework, we show that semi-volatile partitioning can be described in a self-consistent way, with realistic behavior with respect to temperature and varying organic aerosol loading. The time evolution strongly suggests that neglected oxidation of numerous "intermediate volatility" vapors (IVOCs, with saturation concentrations above approximately 1 mg m(-3)) may contribute significantly to ambient SOA formation.

1,214 citations

Journal ArticleDOI
TL;DR: This paper shows that disconnected operation is feasible, efficient and usable by describing its design and implementation in the Coda File System by showing that caching of data, now widely used for performance, can also be exploited to improve availability.
Abstract: Disconnected operation is a mode of operation that enables a client to continue accessing critical data during temporary failures of a shared data repository. An important, though not exclusive, application of disconnected operation is in supporting portable computers. In this paper, we show that disconnected operation is feasible, efficient and usable by describing its design and implementation in the Coda File System. The central idea behind our work is that caching of data, now widely used for performance, can also be exploited to improve availability.

1,214 citations

Journal ArticleDOI
TL;DR: This paper presents a way of specifying types that makes it convenient to define the subtype relation, and discusses the ramifications of this notion of subtyping on the design of type families.
Abstract: The use of hierarchy is an important component of object-oriented design. Hierarchy allows the use of type families, in which higher level supertypes capture the behavior that all of their subtypes have in common. For this methodology to be effective, it is necessary to have a clear understanding of how subtypes and supertypes are related. This paper takes the position that the relationship should ensure that any property proved about supertype objects also holds for its subtype objects. It presents two ways of defining the subtype relation, each of which meets this criterion, and each of which is easy for programmers to use. The subtype relation is based on the specifications of the sub- and supertypes; the paper presents a way of specifying types that makes it convenient to define the subtype relation. The paper also discusses the ramifications of this notion of subtyping on the design of type families.

1,212 citations


Authors

Showing all 36645 results

NameH-indexPapersCitations
Yi Chen2174342293080
Rakesh K. Jain2001467177727
Robert C. Nichol187851162994
Michael I. Jordan1761016216204
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
P. Chang1702154151783
Krzysztof Matyjaszewski1691431128585
Yang Yang1642704144071
Geoffrey E. Hinton157414409047
Herbert A. Simon157745194597
Yongsun Kim1562588145619
Terrence J. Sejnowski155845117382
John B. Goodenough1511064113741
Scott Shenker150454118017
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023120
2022499
20214,980
20205,375
20195,420
20184,972