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Institution

Hewlett-Packard

CompanyPalo Alto, California, United States
About: Hewlett-Packard is a company organization based out in Palo Alto, California, United States. It is known for research contribution in the topics: Signal & Substrate (printing). The organization has 34663 authors who have published 59808 publications receiving 1467218 citations. The organization is also known as: Hewlett Packard & Hewlett-Packard Company.


Papers
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Proceedings ArticleDOI
07 Jun 2008
TL;DR: The simple model the effort to address issues by explicitly providing semantics for threads in the next revision of the C++ standard is described, and how this, together with some practical, but often under-appreciated implementation constraints, drives us towards the above decisions.
Abstract: Currently multi-threaded C or C++ programs combine a single-threaded programming language with a separate threads library. This is not entirely sound [7].We describe an effort, currently nearing completion, to address these issues by explicitly providing semantics for threads in the next revision of the C++ standard. Our approach is similar to that recently followed by Java [25], in that, at least for a well-defined and interesting subset of the language, we give sequentially consistent semantics to programs that do not contain data races. Nonetheless, a number of our decisions are often surprising even to those familiar with the Java effort:We (mostly) insist on sequential consistency for race-free programs, in spite of implementation issues that came to light after the Java work.We give no semantics to programs with data races. There are no benign C++ data races.We use weaker semantics for trylock than existing languages or libraries, allowing us to promise sequential consistency with an intuitive race definition, even for programs with trylock.This paper describes the simple model we would like to be able to provide for C++ threads programmers, and explain how this, together with some practical, but often under-appreciated implementation constraints, drives us towards the above decisions.

491 citations

Journal ArticleDOI
TL;DR: This method is based on notions of voltage drops across networks that are both intuitive and easy to solve regardless of the complexity of the graph involved and allows for the swift discovery of the community surrounding a given node.
Abstract: We present a method that allows for the discovery of communities within graphs of arbitrary size in times that scale linearly with their size. This method avoids edge cutting and is based on notions of voltage drops across networks that are both intuitive and easy to solve regardless of the complexity of the graph involved. We additionally show how this algorithm allows for the swift discovery of the community surrounding a given node without having to extract all the communities out of a graph.

488 citations

Book ChapterDOI
01 Jan 2003
TL;DR: In this paper, the authors describe a method for the automatic identification of communities of practice from email logs within an organization using a betweenness centrality algorithm that can rapidly find communities within a graph representing information flows.
Abstract: We describe a method for the automatic identification of communities of practice from email logs within an organization. We use a betweenness centrality algorithm that can rapidly find communities within a graph representing information flows. We apply this algorithm to an email corpus of nearly one million messages collected over a two-month span, and show that the method is effective at identifying true communities, both formal and informal, within these scale-free graphs. This approach also enables the identification of leadership roles within the communities. These studies are complemented by a qualitative evaluation of the results in the field.

486 citations

Journal ArticleDOI
TL;DR: It is shown that, in certain applications, rightful ownership cannot be resolved by current watermarking schemes alone, and existing techniques are attacked by providing counterfeit water marking schemes that can be performed on a watermarked image to allow multiple claims of rightful ownership.
Abstract: Digital watermarks have been proposed as a means for copyright protection of multimedia data. We address the capability of invisible watermarking schemes to resolve copyright ownership. We show that, in certain applications, rightful ownership cannot be resolved by current watermarking schemes alone. Specifically, we attack existing techniques by providing counterfeit watermarking schemes that can be performed on a watermarked image to allow multiple claims of rightful ownership. In the absence of standardization and specific requirements imposed on watermarking procedures, anyone can claim ownership of any watermarked image. In order to protect against the counterfeiting techniques that we develop, we examine the properties necessary for resolving ownership via invisible watermarking. We introduce and study invertibility and quasi-invertibility of invisible watermarking techniques. We propose noninvertible watermarking schemes, and subsequently give examples of techniques that we believe to be nonquasi-invertible and hence invulnerable against more sophisticated attacks proposed in the paper. The attacks and results presented in the paper, and the remedies proposed, further imply that we have to carefully reevaluate the current approaches and techniques in invisible watermarking of digital images based on application domains, and rethink the promises, applications and implications of such digital means of copyright protection.

481 citations

Book
06 Jun 1987
TL;DR: This dissertation is the most detailed study of a metrics program ever done.
Abstract: For Grad level courses in software engineering, software development and software metrics. Explains what metrics are and when they are useful. Most detailed study of a metrics program ever done.

480 citations


Authors

Showing all 34676 results

NameH-indexPapersCitations
Andrew White1491494113874
Stephen R. Forrest1481041111816
Rafi Ahmed14663393190
Leonidas J. Guibas12469179200
Chenming Hu119129657264
Robert E. Tarjan11440067305
Hong-Jiang Zhang11246149068
Ching-Ping Wong106112842835
Guillermo Sapiro10466770128
James R. Heath10342558548
Arun Majumdar10245952464
Luca Benini101145347862
R. Stanley Williams10060546448
David M. Blei98378111547
Wei-Ying Ma9746440914
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202223
2021240
20201,028
20191,269
2018964