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Modular elliptic curves and Fermat’s Last Theorem
 ANNALS OF MATH
, 1995
"... When Andrew John Wiles was 10 years old, he read Eric Temple Bell’s The Last Problem and was so impressed by it that he decided that he would be the first person to prove Fermat’s Last Theorem. This theorem states that there are no nonzero integers a, b, c, n with n> 2 such that a n + b n = c n ..."
Abstract

Cited by 617 (2 self)
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When Andrew John Wiles was 10 years old, he read Eric Temple Bell’s The Last Problem and was so impressed by it that he decided that he would be the first person to prove Fermat’s Last Theorem. This theorem states that there are no nonzero integers a, b, c, n with n> 2 such that a n + b n = c
Tabu Search  Part II
, 1990
"... This is the second half of a two part series devoted to the tabu search metastrategy for optimization problems. Part I introduced the fundamental ideas of tabu search as an approach for guiding other heuristics to overcome the limitations of local optimality, both in a deterministic and a probabilis ..."
Abstract

Cited by 387 (5 self)
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refinements and more advanced aspects of tabu search. Following a brief review of notation, Part I1 introduces new dynamic strategies for managing tabu lists, allowing fuller exploitation of underlying evaluation functions. In turn, the elements of staged search and structured move sets are characterized
Integers
"... Summary. In the article the following concepts were introduced: the set of integers (Z) and its elements (integers), congruences (i1 ≡ i2(modi3)), the ceiling and floor functors (⌈x ⌉ and ⌊x⌋), also the fraction part of a real number (frac), the integer division (÷) and remainder of integer division ..."
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Summary. In the article the following concepts were introduced: the set of integers (Z) and its elements (integers), congruences (i1 ≡ i2(modi3)), the ceiling and floor functors (⌈x ⌉ and ⌊x⌋), also the fraction part of a real number (frac), the integer division (÷) and remainder of integer
Integers
"... Summary. In the article the following concepts were introduced: the set of integers ( ) and its elements (integers), congruences (i1 ≡ i2(mod i3)), the ceiling and floor functors (⌈x ⌉ and ⌊x⌋), also the fraction part of a real number (frac), the integer division (÷) and remainder of integer divis ..."
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Summary. In the article the following concepts were introduced: the set of integers ( ) and its elements (integers), congruences (i1 ≡ i2(mod i3)), the ceiling and floor functors (⌈x ⌉ and ⌊x⌋), also the fraction part of a real number (frac), the integer division (÷) and remainder of integer
INTEGER
"... Note: before using this routine, please read the Users ’ Note for your implementation to check the interpretation of bold italicised terms and other implementationdependent details. 1 Purpose E04YCF returns estimates of elements of the variancecovariance matrix of the estimated regression coeffici ..."
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coefficients for a nonlinear least squares problem. The estimates are derived from the Jacobian of the function fx ð Þ at the solution. This routine may be used following any one of the nonlinear least squares routines E04FCF, E04FYF,
Integers
"... This paper deals with the identification of effective masses and modal masses from basedriven tests. When performing a basedriven test with an elastomechanical structure. the structural responses can be related to the base ac&rations and a modal identification of the structure can be accompl ..."
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be accomplished. If, in addition, the base forces are measured, it is possible to determine the effective and modal masses of the structure. Here, the required equations describing the dynamic behaviour are first developed and discussed. In the following, an analytical vibration system with simulated measurement
Pyramidal implementation of the Lucas Kanade feature tracker
 Intel Corporation, Microprocessor Research Labs
, 2000
"... grayscale value of the two images are the location x = [x y] T, where x and y are the two pixel coordinates of a generic image point x. The image I will sometimes be referenced as the first image, and the image J as the second image. For practical issues, the images I and J are discret function (or ..."
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Cited by 308 (0 self)
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ωx and ωy two integers. We define the image velocity d as being the vector that minimizes the residual function ɛ defined as follows: ɛ(d) = ɛ(dx, dy) = ux+ωx ∑ uy+ωy x=ux−ωx y=uy−ωy (I(x, y) − J(x + dx, y + dy)) 2. (1)
Approximation Algorithms for Projective Clustering
 Proceedings of the ACM SIGMOD International Conference on Management of data, Philadelphia
, 2000
"... We consider the following two instances of the projective clustering problem: Given a set S of n points in R d and an integer k ? 0; cover S by k hyperstrips (resp. hypercylinders) so that the maximum width of a hyperstrip (resp., the maximum diameter of a hypercylinder) is minimized. Let w ..."
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Cited by 302 (22 self)
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We consider the following two instances of the projective clustering problem: Given a set S of n points in R d and an integer k ? 0; cover S by k hyperstrips (resp. hypercylinders) so that the maximum width of a hyperstrip (resp., the maximum diameter of a hypercylinder) is minimized. Let w
Maintaining Stream Statistics over Sliding Windows (Extended Abstract)
, 2002
"... We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding window model. We consider the following basic problem: Given a stream of bits, maintain a count of the number of 1's i ..."
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Cited by 269 (9 self)
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We consider the problem of maintaining aggregates and statistics over data streams, with respect to the last N data elements seen so far. We refer to this model as the sliding window model. We consider the following basic problem: Given a stream of bits, maintain a count of the number of 1&apos
APPROXIMATION ALGORITHMS FOR SCHEDULING UNRELATED PARALLEL MACHINES
, 1990
"... We consider the following scheduling problem. There are m parallel machines and n independent.jobs. Each job is to be assigned to one of the machines. The processing of.job j on machine i requires time Pip The objective is to lind a schedule that minimizes the makespan. Our main result is a polynomi ..."
Abstract

Cited by 265 (7 self)
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We consider the following scheduling problem. There are m parallel machines and n independent.jobs. Each job is to be assigned to one of the machines. The processing of.job j on machine i requires time Pip The objective is to lind a schedule that minimizes the makespan. Our main result is a
Results 1  10
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