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INEQUALITIES FOR CHAINS OF NORMALIZED SYMMETRIC SUMS
, 2008
"... ABSTRACT. In this paper we prove some inequalities between expressions of the following form: ai1 + · · · + aik a1 + · · · + an − (ai1 + · · · + aik), 1≤i1<···<ik≤n where a1, · · · , an are positive numbers and k, n ∈ N, k < n. Using the results in [1] which show that () n n−k k ..."
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ABSTRACT. In this paper we prove some inequalities between expressions of the following form: ai1 + · · · + aik a1 + · · · + an − (ai1 + · · · + aik), 1≤i1<···<ik≤n where a1, · · · , an are positive numbers and k, n ∈ N, k < n. Using the results in [1] which show that () n n−k k
Creative Commons Attribution License. Multiparty Symmetric Sum Types
"... Abstract This paper introduces a new theory of multiparty session types based on symmetric sum types, by which we can type nondeterministic orchestration choice behaviours. While the original branching type in session types can represent a choice made by a single participant and accepted by others ..."
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Abstract This paper introduces a new theory of multiparty session types based on symmetric sum types, by which we can type nondeterministic orchestration choice behaviours. While the original branching type in session types can represent a choice made by a single participant and accepted by others
Symmetric SumFree Partitions and Lower Bounds for Schur Numbers
, 2000
"... We give new lower bounds for the Schur numbers S(6) and S(7). This will imply new lower bounds for the Multicolor Ramsey Numbers R6(3) and R7(3). We also make several observations concerning symmetric sumfree partitions into 5 sets. ..."
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We give new lower bounds for the Schur numbers S(6) and S(7). This will imply new lower bounds for the Multicolor Ramsey Numbers R6(3) and R7(3). We also make several observations concerning symmetric sumfree partitions into 5 sets.
Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones
, 1998
"... SeDuMi is an addon for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity. This pape ..."
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Cited by 1334 (4 self)
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SeDuMi is an addon for MATLAB, that lets you solve optimization problems with linear, quadratic and semidefiniteness constraints. It is possible to have complex valued data and variables in SeDuMi. Moreover, large scale optimization problems are solved efficiently, by exploiting sparsity. This paper describes how to work with this toolbox.
Symmetric SumFree Partitions and Lower Bounds for Schur Numbers
 Electronic Journal of Combinatorics
, 2000
"... We give new lower bounds for the Schur numbers S(6) and S(7). This will imply new lower bounds for the Multicolor Ramsey Numbers R6(3) and R7(3). We also make several observations concerning symmetric sumfree partitions into 5 sets. ..."
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Cited by 12 (0 self)
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We give new lower bounds for the Schur numbers S(6) and S(7). This will imply new lower bounds for the Multicolor Ramsey Numbers R6(3) and R7(3). We also make several observations concerning symmetric sumfree partitions into 5 sets.
Good ErrorCorrecting Codes based on Very Sparse Matrices
, 1999
"... We study two families of errorcorrecting codes defined in terms of very sparse matrices. "MN" (MacKayNeal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The ..."
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Cited by 741 (23 self)
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. The decoding of both codes can be tackled with a practical sumproduct algorithm. We prove that these codes are "very good," in that sequences of codes exist which, when optimally decoded, achieve information rates up to the Shannon limit. This result holds not only for the binarysymmetric channel
This work is licensed under the Creative Commons Attribution License. Multiparty Symmetric Sum Types
"... Abstract This paper introduces a new theory of multiparty session types based on symmetric sum types, by which we can type nondeterministic orchestration choice behaviours. While the original branching type in session types can represent a choice made by a single participant and accepted by others ..."
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Abstract This paper introduces a new theory of multiparty session types based on symmetric sum types, by which we can type nondeterministic orchestration choice behaviours. While the original branching type in session types can represent a choice made by a single participant and accepted by others
Symmetry and Related Properties via the Maximum Principle
, 1979
"... We prove symmetry, and some related properties, of positive solutions of second order elliptic equations. Our methods employ various forms of the maximum principle, and a device of moving parallel planes to a critical position, and then showing that the solution is symmetric about the limiting plan ..."
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Cited by 539 (4 self)
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We prove symmetry, and some related properties, of positive solutions of second order elliptic equations. Our methods employ various forms of the maximum principle, and a device of moving parallel planes to a critical position, and then showing that the solution is symmetric about the limiting
Closedform solution of absolute orientation using unit quaternions
 J. Opt. Soc. Am. A
, 1987
"... Finding the relationship between two coordinate systems using pairs of measurements of the coordinates of a number of points in both systems is a classic photogrammetric task. It finds applications in stereophotogrammetry and in robotics. I present here a closedform solution to the leastsquares pr ..."
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Cited by 973 (4 self)
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. These exact results are to be preferred to approximate methods based on measurements of a few selected points. The unit quaternion representing the best rotation is the eigenvector associated with the most positive eigenvalue of a symmetric 4 X 4 matrix. The elements of this matrix are combinations of sums
Detection and Tracking of Point Features
 International Journal of Computer Vision
, 1991
"... The factorization method described in this series of reports requires an algorithm to track the motion of features in an image stream. Given the small interframe displacement made possible by the factorization approach, the best tracking method turns out to be the one proposed by Lucas and Kanade i ..."
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Cited by 622 (2 self)
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in 1981. The method defines the measure of match between fixedsize feature windows in the past and current frame as the sum of squared intensity differences over the windows. The displacement is then defined as the one that minimizes this sum. For small motions, a linearization of the image intensities
Results 1  10
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