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Ktheory for operator algebras
 Mathematical Sciences Research Institute Publications
, 1998
"... p. XII line5: since p. 12: I blew this simple formula: should be α = −〈ξ, η〉/〈η, η〉. p. 2 I.1.1.4: The RieszFischer Theorem is often stated this way today, but neither Riesz nor Fischer (who worked independently) phrased it in terms of completeness of the orthogonal system {e int}. If [a, b] is a ..."
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Cited by 559 (0 self)
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space is not σfinite. p. 13: add after I.2.6.16: I.2.6.17. If X is a compact subset of C not containing 0, and k ∈ N, there is in general no bound on the norm of T −1 as T ranges over all operators with ‖T ‖ ≤ k and σ(T) ⊆ X. For example, let Sn ∈ L(l 2) be the truncated shift: Sn(α1, α2,...) = (0
ℓdiversity: Privacy beyond kanonymity
 IN ICDE
, 2006
"... Publishing data about individuals without revealing sensitive information about them is an important problem. In recent years, a new definition of privacy called kanonymity has gained popularity. In a kanonymized dataset, each record is indistinguishable from at least k − 1 other records with resp ..."
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Cited by 649 (12 self)
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Publishing data about individuals without revealing sensitive information about them is an important problem. In recent years, a new definition of privacy called kanonymity has gained popularity. In a kanonymized dataset, each record is indistinguishable from at least k − 1 other records
The complete genome sequence of Escherichia coli K12
 Science
, 1997
"... The 4,639,221–base pair sequence of Escherichia coli K12 is presented. Of 4288 proteincoding genes annotated, 38 percent have no attributed function. Comparison with five other sequenced microbes reveals ubiquitous as well as narrowly distributed gene families; many families of similar genes withi ..."
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Cited by 1106 (39 self)
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, and biotechnology, E. coli K12 was the earliest organism to be suggested as a candidate for whole genome
KSVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
, 2006
"... In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signalatoms, signals are described by sparse linear combinations of these atoms. Applications that use sparse representation are many and inc ..."
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Cited by 930 (41 self)
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signal representations. Given a set of training signals, we seek the dictionary that leads to the best representation for each member in this set, under strict sparsity constraints. We present a new method—the KSVD algorithm—generalizing the umeans clustering process. KSVD is an iterative method
A comparison of document clustering techniques
 In KDD Workshop on Text Mining
, 2000
"... This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and Kmeans. (We used both a “standard” Kmeans algorithm and a “bisecting ” Kmeans algorithm.) Our results indicate that the bisecting Kmeans technique is ..."
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Cited by 600 (29 self)
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This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and Kmeans. (We used both a “standard” Kmeans algorithm and a “bisecting ” Kmeans algorithm.) Our results indicate that the bisecting Kmeans technique
The fundamental properties of natural numbers
 Journal of Formalized Mathematics
, 1989
"... Summary. Some fundamental properties of addition, multiplication, order relations, exact division, the remainder, divisibility, the least common multiple, the greatest common divisor are presented. A proof of Euclid algorithm is also given. MML Identifier:NAT_1. WWW:http://mizar.org/JFM/Vol1/nat_1.h ..."
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Cited by 682 (76 self)
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.html The articles [4], [6], [1], [2], [5], and [3] provide the notation and terminology for this paper. A natural number is an element of N. For simplicity, we use the following convention: x is a real number, k, l, m, n are natural numbers, h, i, j are natural numbers, and X is a subset of R
Depth first search and linear graph algorithms
 SIAM JOURNAL ON COMPUTING
, 1972
"... The value of depthfirst search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
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Cited by 1384 (19 self)
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of an undirect graph are presented. The space and time requirements of both algorithms are bounded by k 1V + k2E d k for some constants kl, k2, and k a, where Vis the number of vertices and E is the number of edges of the graph being examined.
Some methods for classification and analysis of multivariate observations
 In 5th Berkeley Symposium on Mathematical Statistics and Probability
, 1967
"... The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably ..."
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Cited by 2983 (3 self)
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The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably
Construction of Escherichia coli K12 inframe, singlegene knockout mutants: the Keio collection. Mol. Syst. Biol 2:2006.0008
, 2006
"... We have systematically made a set of precisely defined, singlegene deletions of all nonessential genes in Escherichia coli K12. Openreading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a onestep method for inactivation of chromosom ..."
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Cited by 701 (7 self)
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We have systematically made a set of precisely defined, singlegene deletions of all nonessential genes in Escherichia coli K12. Openreading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a onestep method for inactivation
A ReExamination of Text Categorization Methods
, 1999
"... This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a kNearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We f ..."
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Cited by 832 (24 self)
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This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a kNearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We
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