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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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Patent
Qian Lin1
12 Feb 2002
TL;DR: In this paper, a method for assessing the photo quality of a captured image in a digital camera comprises the steps of checking in-camera the quality of the captured image to determine if photo quality is acceptable, and providing a corresponding photo quality feedback to a camera user.
Abstract: A method for assessing the photo quality of a captured image in a digital camera comprises the steps of checking in-camera the photo quality of the captured image to determine if the photo quality is acceptable, and providing a corresponding photo quality feedback to a camera user.

207 citations

Journal ArticleDOI
TL;DR: Aliasing has been a problem in both formal verification and practical programming for a number of years as discussed by the authors, and it can result in mysterious bugs as variables change their values seemingly on their own.
Abstract: Aliasing has been a problem in both formal verification and practical programming for a number of years. To the formalist, it can be annoyingly difficult to prove the simple Hoare formula {x = true} y := false {x = true}. If x and y refer to the same boolean variable, i.e., x and y are aliased, then the formula will not be valid, and proving that aliasing cannot occur is not always straightforward. To the practicing programmer, aliases can result in mysterious bugs as variables change their values seemingly on their own. A classic example is the matrix multiply routine mult(left, right, result) which puts the product of its first two parameters into the third. This works perfectly well until the day some unsuspecting programmer writes the very reasonable statement mult(a, b, a). If the implementor of the routine did not consider the possibility that an argument may be aliased with the result, disaster is inevitable.

207 citations

Proceedings ArticleDOI
Wei-Ying Ma1, Ilja Bedner1, Grace Chang1, Allan Kuchinsky1, Hong-Jiang Zhang1 
27 Dec 1999
TL;DR: This paper proposes a framework for adaptive content delivery in heterogeneous environments that includes content adaptation algorithms, client capability and network bandwidth discovery methods, and a Decision Engine for determining when and how to adapt content.
Abstract: The explosive growth of the Internet has come with increasing diversity and heterogeneity in terms of client device capability, network bandwidth, and user preferences. To date, most Web content has been designed with desktop computers in mind, and often contains rich media such as images, audio, and video. In many cases, this content is not suitable for devices like netTVs, handheld computers, personal digital assistants, and smart phones with relatively limited display capability, storage, processing power, and network access. Thus, Internet access is still constrained on these devices and there is a need to develop alternative approaches for information delivery. In this paper, we propose a framework for adaptive content delivery in heterogeneous environments. The goal is to improve content accessibility and perceived quality of service for information access under changing network and viewer conditions. The framework includes content adaptation algorithms, client capability and network bandwidth discovery methods, and a Decision Engine for determining when and how to adapt content. We describe this framework, initial system implementations based upon this framework, and the issues associated with the deployment of such systems based on different architectures.

207 citations

Patent
03 Nov 1997
TL;DR: In this paper, a digital image management system is described that includes a content analyzer that analyzes an image to extract content data from the image, which include face feature data.
Abstract: A digital image management system is described that includes a content analyzer that analyzes an image to extract content data from the image. The content data of an image include face feature data. The digital image management system also includes an image database that is coupled to the content analyzer to store pixel data of each of a number of images and the content data of each of the images. A search engine is also provided in the digital image management system. The search engine is coupled to the image database and the content analyzer to compare the content data of the images with that of an input image such that any image similar to the input image can be identified from the image database without retrieving the pixel data of the image from the image database. A method of extracting feature data of a face in an image is also described.

207 citations

Proceedings ArticleDOI
21 Apr 2008
TL;DR: With sniping and parameter tuning enabled, the budget-constrained bidding optimization problem for sponsored search auctions is considered, and the bidding algorithms can achieve a performance ratio above 90% against the optimum by the omniscient bidder.
Abstract: We consider the budget-constrained bidding optimization problem for sponsored search auctions, and model it as an online (multiple-choice) knapsack problem. We design both deterministic and randomized algorithms for the online (multiple-choice) knapsack problems achieving a provably optimal competitive ratio. This translates back to fully automatic bidding strategies maximizing either profit or revenue for the budget-constrained advertiser. Our bidding strategy for revenue maximization is oblivious (i.e., without knowledge) of other bidders' prices and/or click-through-rates for those positions. We evaluate our bidding algorithms using both synthetic data and real bidding data gathered manually, and also discuss a sniping heuristic that strictly improves bidding performance. With sniping and parameter tuning enabled, our bidding algorithms can achieve a performance ratio above 90% against the optimum by the omniscient bidder.

207 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