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753
Searching in metric spaces
, 2001
"... The problem of searching the elements of a set that are close to a given query element under some similarity criterion has a vast number of applications in many branches of computer science, from pattern recognition to textual and multimedia information retrieval. We are interested in the rather gen ..."
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Cited by 432 (38 self)
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The problem of searching the elements of a set that are close to a given query element under some similarity criterion has a vast number of applications in many branches of computer science, from pattern recognition to textual and multimedia information retrieval. We are interested in the rather general case where the similarity criterion defines a metric space, instead of the more restricted case of a vector space. Many solutions have been proposed in different areas, in many cases without crossknowledge. Because of this, the same ideas have been reconceived several times, and very different presentations have been given for the same approaches. We present some basic results that explain the intrinsic difficulty of the search problem. This includes a quantitative definition of the elusive concept of “intrinsic dimensionality. ” We also present a unified
Kalantari “ Acceleration of distributed Minimax flow Optimization
 in Networks “ in the proceedings of 2011 IEEE
"... AbstractA single commodity network with multiple sources and sinks is modeled by a graph, where a vertex represents a node and a link between two connected nodes is modeled by a weighted edge. The weight of an edge represents the capacity of the link. We provide a distributed method to assign a flo ..."
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Cited by 1 (0 self)
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AbstractA single commodity network with multiple sources and sinks is modeled by a graph, where a vertex represents a node and a link between two connected nodes is modeled by a weighted edge. The weight of an edge represents the capacity of the link. We provide a distributed method to assign a flow to each link such that the traffic flows generated by the sources reach the sinks while a specific convex cost function, namely the pnorm of the network flow, is minimized. As p t 00 the flow optimizes the minimax cost function in the network, i.e., the traffic flow is assigned to the links such that the traffic on the most utilized link is minimized, while the network flow is conserved. It is shown that with a given network configuration and channel capacities, the flow allocation based on optimizing the minimax cost function results in the largest set of feasible source traffic rates, i.e., if it is feasible to route a set of sources to a set of destinations in the network, then the minimax flow allocation will achieve it. Our proposed method for finding the optimal flow involves iterations that minimize a quadratic approximation of the cost function in each step. We show that all of the steps for finding the optimal flow can be implemented distributedly, where instead of a centralized network controller, the nodes iteratively use the local state information of their neighbors to update their output flow. We propose an algorithm that accelerates the convergence of iterations significantly, and compare it with other acceleration methods.
Numerical Evaluation and Comparison of Kalantari’s Zero Bounds for Complex Polynomials
, 2014
"... In this paper, we investigate the performance of zero bounds due to Kalantari and Dehmer by using special classes of polynomials. Our findings are evidenced by numerical as well as analytical results. ..."
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In this paper, we investigate the performance of zero bounds due to Kalantari and Dehmer by using special classes of polynomials. Our findings are evidenced by numerical as well as analytical results.
ON EFFICIENT COMPUTATION AND ASYMPTOTIC SHARPNESS OF KALANTARI’S BOUNDS FOR ZEROS OF POLYNOMIALS
"... Abstract. We study an infinite family of lower and upper bounds on the modulus of zeros of complex polynomials derived by Kalantari. We first give a simple characterization of these bounds which leads to an efficient algorithm for their computation. For a polynomial of degree n our algorithm compute ..."
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Cited by 1 (1 self)
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computes the first m bounds in Kalantari’s family in O(mn) operations. We further prove that for every complex polynomial these lower and upper bounds converge to the tightest annulus containing the roots, and thus settle a problem raised in Kalantari’s paper. 1.
Indexdriven similarity search in metric spaces
 ACM Transactions on Database Systems
, 2003
"... Similarity search is a very important operation in multimedia databases and other database applications involving complex objects, and involves finding objects in a data set S similar to a query object q, based on some similarity measure. In this article, we focus on methods for similarity search th ..."
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Cited by 184 (7 self)
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Similarity search is a very important operation in multimedia databases and other database applications involving complex objects, and involves finding objects in a data set S similar to a query object q, based on some similarity measure. In this article, we focus on methods for similarity search that make the general assumption that similarity is represented with a distance metric d. Existing methods for handling similarity search in this setting typically fall into one of two classes. The first directly indexes the objects based on distances (distancebased indexing), while the second is based on mapping to a vector space (mappingbased approach). The main part of this article is dedicated to a survey of distancebased indexing methods, but we also briefly outline how search occurs in mappingbased methods. We also present a general framework for performing search based on distances, and present algorithms for common types of queries that operate on an arbitrary “search hierarchy. ” These algorithms can be applied on each of the methods presented, provided a suitable search hierarchy is defined.
Research Article The Novel Diagnostic Biomarkers for Focal Segmental Glomerulosclerosis Mohsen Nafar,1,2,3 Shiva Kalantari,4 Shiva Samavat,1,2,3 Mostafa RezaeiTavirani,5
"... Copyright © 2014 Mohsen Nafar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Focal segmental glomerulosclerosis ( ..."
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Copyright © 2014 Mohsen Nafar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Focal segmental glomerulosclerosis (FSGS) is a glomerular injury with various pathogenic mechanisms. Urine proteome panel might help in noninvasive diagnosis and better understanding of pathogenesis of FSGS.Method. We have analyzed the urine sample of 11 biopsyproven FSGS subjects, 8 healthy controls, and 6 patients with biopsyproven IgA nephropathy (disease controls) bymeans of liquid chromatography tandemmass spectrometry (nLCMS/MS).Multivariate analysis of quantified proteins was performed by principal component analysis (PCA) and partial least squares (PLS). Results. Of the total number of 389 proteins, after multivariate analysis and additional filter criterion and comparing FSGS versus IgA nephropathy and healthy subjects, 77 proteins were considered as putative biomarkers of FSGS. CD59, CD44, IBP7, Robo4, and DPEP1 were the most significant differentially expressed proteins. These proteins are involved in pathogenic pathways: complement pathway, sclerosis, cell proliferation, actin cytoskeleton remodeling, and activity of TRPC6.There was complete absence of DPEP1 in urine proteome
Newton's Method and Generation of a Determinantal Family of Iteration Functions
, 1998
"... It is wellknown that Halley's method can be obtained by applying Newton's method to the function f/ # f # . Gerlach [3], gives a generalization of this approach, and for each m # 2, recursively defines an iteration function Gm (x) having order m. Kalantari et al. [6], and Kalantari [8] ..."
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Cited by 7 (7 self)
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It is wellknown that Halley's method can be obtained by applying Newton's method to the function f/ # f # . Gerlach [3], gives a generalization of this approach, and for each m # 2, recursively defines an iteration function Gm (x) having order m. Kalantari et al. [6], and Kalantari [8
Quadratic Optimization
, 1995
"... . Quadratic optimization comprises one of the most important areas of nonlinear programming. Numerous problems in real world applications, including problems in planning and scheduling, economies of scale, and engineering design, and control are naturally expressed as quadratic problems. Moreover, t ..."
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Cited by 61 (3 self)
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. Quadratic optimization comprises one of the most important areas of nonlinear programming. Numerous problems in real world applications, including problems in planning and scheduling, economies of scale, and engineering design, and control are naturally expressed as quadratic problems. Moreover, the quadratic problem is known to be NPhard, which makes this one of the most interesting and challenging class of optimization problems. In this chapter, we review various properties of the quadratic problem, and discuss different techniques for solving various classes of quadratic problems. Some of the more successful algorithms for solving the special cases of bound constrained and large scale quadratic problems are considered. Examples of various applications of quadratic programming are presented. A summary of the available computational results for the algorithms to solve the various classes of problems is presented. Key words: Quadratic optimization, bilinear programming, concave pro...
Solving Quadratic (0,1)Problems by Semidefinite Programs and Cutting Planes
, 1996
"... We present computational experiments for solving quadratic (0, 1) problems. Our approach combines a semidefinite relaxation with a cutting plane technique, and is applied in a Branch and Bound setting. Our experiments indicate that this type of approach is very robust, and allows to solve many moder ..."
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Cited by 60 (7 self)
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We present computational experiments for solving quadratic (0, 1) problems. Our approach combines a semidefinite relaxation with a cutting plane technique, and is applied in a Branch and Bound setting. Our experiments indicate that this type of approach is very robust, and allows to solve many moderately sized problems, having say, less than 100 binary variables, in a routine manner.
Heuristic Algorithms for the Unconstrained Binary Quadratic Programming Problem
, 1998
"... In this paper we consider the unconstrained binary quadratic programming problem. This is the problem of maximising a quadratic objective by suitable choice of binary (zeroone) variables. We present two heuristic algorithms based upon tabu search and simulated annealing for this problem. Computatio ..."
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Cited by 41 (0 self)
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In this paper we consider the unconstrained binary quadratic programming problem. This is the problem of maximising a quadratic objective by suitable choice of binary (zeroone) variables. We present two heuristic algorithms based upon tabu search and simulated annealing for this problem
Results 1  10
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