Institution
IBM
Company•Armonk, New York, United States•
About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Cache. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.
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IBM1
TL;DR: Geographical curves are so involved in their detail that their lengths are often infinite or, rather, undefinable; however, many are statistically "selfsimilar," meaning that each portion can be considered a reduced-scale image of the whole.
Abstract: Geographical curves are so involved in their detail that their lengths are often infinite or, rather, undefinable. However, many are statistically "selfsimilar," meaning that each portion can be considered a reduced-scale image of the whole. In that case, the degree of complication can be described by a quantity D that has many properties of a "dimension," though it is fractional; that is, it exceeds the value unity associated with the ordinary, rectifiable, curves.
3,222 citations
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IBM1
TL;DR: Information systems architecture is defined by creating a descriptive framework from disciplines quite independent of information systems, then by analogy specifies information systems architecture based upon the neutral, objective framework.
Abstract: With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems architecture by creating a descriptive framework from disciplines quite independent of information systems, then by analogy specifies information systems architecture based upon the neutral, objective framework. Also, some preliminary conclusions about the implications of the resultant descriptive framework are drawn. The discussion is limited to architecture and does not include a strategic planning methodology.
3,219 citations
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IBM1
TL;DR: In this article, the authors reviewed the calculation of the stopping and the final range distribution of ions in matter, and showed the development of ion penetration theory by tracing how, as the theory developed through the years, various parts have been incorporated into tables and increased their accuracy.
Abstract: The purpose of this chapter is to review the calculation f the stopping and the final range distribution of ions in matter. During the last thirty years there have been published scores of tables and books evaluating the parameters of energetic ion penetration of matter. Rarely have the authors of these reference works included any evaluation of the accuracy of the tabulated numbers. We have chosen to show the development of ion penetration theory by tracing how, as the theory developed through the years, various parts have been incorporated into tables and increased their accuracy. This approach restricts our comments to those theoretical advances which have made significant contributions to the obtaining of practical ion stopping powers and range distributions. The Tables reviewed were chosen because of their extensive citation in the literature.
3,197 citations
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IBM1
TL;DR: In this paper, it was shown that the interfaces between layers were made up of large coherent areas separated by long straight misfit dislocations and the Burgers vectors were inclined at 45° to (001) and were of type 1/2a.
3,179 citations
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IBM1
TL;DR: This work considers the concrete case of building a decision-tree classifier from training data in which the values of individual records have been perturbed and proposes a novel reconstruction procedure to accurately estimate the distribution of original data values.
Abstract: A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Specifically, we address the following question. Since the primary task in data mining is the development of models about aggregated data, can we develop accurate models without access to precise information in individual data records? We consider the concrete case of building a decision-tree classifier from training data in which the values of individual records have been perturbed. The resulting data records look very different from the original records and the distribution of data values is also very different from the original distribution. While it is not possible to accurately estimate original values in individual data records, we propose a novel reconstruction procedure to accurately estimate the distribution of original data values. By using these reconstructed distributions, we are able to build classifiers whose accuracy is comparable to the accuracy of classifiers built with the original data.
3,173 citations
Authors
Showing all 134658 results
Name | H-index | Papers | Citations |
---|---|---|---|
Zhong Lin Wang | 245 | 2529 | 259003 |
Anil K. Jain | 183 | 1016 | 192151 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Rodney S. Ruoff | 164 | 666 | 194902 |
Tobin J. Marks | 159 | 1621 | 111604 |
Jean M. J. Fréchet | 154 | 726 | 90295 |
Albert-László Barabási | 152 | 438 | 200119 |
György Buzsáki | 150 | 446 | 96433 |
Stanislas Dehaene | 149 | 456 | 86539 |
Philip S. Yu | 148 | 1914 | 107374 |
James M. Tour | 143 | 859 | 91364 |
Thomas P. Russell | 141 | 1012 | 80055 |
Naomi J. Halas | 140 | 435 | 82040 |
Steven G. Louie | 137 | 777 | 88794 |
Daphne Koller | 135 | 367 | 71073 |