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Property Testing and its connection to Learning and Approximation
"... We study the question of determining whether an unknown function has a particular property or is fflfar from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query the fun ..."
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Cited by 475 (67 self)
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We study the question of determining whether an unknown function has a particular property or is fflfar from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query
The case of lambda expressions (Rule 17) shows how memory allocation is handled.
"... e 3 ]]ffl 3 ae = E [[e]]ae(single ffl: F [[e 3 ]](ffl 3 x hffli)ae) The justification for Rule 4 is also derived from the definition of F . F [[ ]]ffl 3 ae = ffl 3 Another nonobvious case is the case of allocating a list for rest arguments (Rules 1314). Their justifications can be de ..."
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e 3 ]]ffl 3 ae = E [[e]]ae(single ffl: F [[e 3 ]](ffl 3 x hffli)ae) The justification for Rule 4 is also derived from the definition of F . F [[ ]]ffl 3 ae = ffl 3 Another nonobvious case is the case of allocating a list for rest arguments (Rules 1314). Their justifications can
Blind Channel Equalization and fflApproximation Algorithms
"... Abstract In this paper, we show that a blind equalizer can be obtained without using any statistical information on the input by formulating the blind channel equalization problem into a quadratic optimization with binary constraints. Then, efficient fflapproximation algorithms are presented and ap ..."
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Abstract In this paper, we show that a blind equalizer can be obtained without using any statistical information on the input by formulating the blind channel equalization problem into a quadratic optimization with binary constraints. Then, efficient fflapproximation algorithms are presented
Computing a (1 + ffl)Approximate Geometric MinimumDiameter Spanning Tree
, 2003
"... Abstract Given a set P of points in the plane, a geometric minimumdiameter spanning tree (GMDST)of P is a spanning tree of P such that the longest path through the tree is minimized. Forseveral years, the best upper bound on the time to compute a GMDST was cubic with respect to the number of points ..."
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of points in the input set. Recently, Timothy Chan introduced a subcubic timealgorithm. In this paper, we present an algorithm that generates a tree whose diameter is no more than (1 + ffl) times that of a GMDST, for any ffl> 0. Our algorithm reduces the problem toseveral gridaligned versions
Homogeneous InteriorPoint Algorithms for Semidefinite Programming
 Department of Mathematics, The University of Iowa
, 1995
"... A simple homogeneous primaldual feasibility model is proposed for semidefinite programming (SDP) problems. Two infeasibleinteriorpoint algorithms are applied to the homogeneous formulation. The algorithms do not need big M initialization. If the original SDP problem has a solution, then both algo ..."
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Cited by 37 (8 self)
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algorithms find an fflapproximate solution (i.e., a solution with residual error less than or equal to ffl) in at most O( p n ln(ae ffl 0 =ffl)) steps, where ae is the trace norm of a solution and ffl 0 is the residual error at the (normalized) starting point. A simple way of monitoring possible
Approximate Nearest Neighbor Queries in Fixed Dimensions
, 1993
"... Given a set of n points in ddimensional Euclidean space, S ae E d , and a query point q 2 E d , we wish to determine the nearest neighbor of q, that is, the point of S whose Euclidean distance to q is minimum. The goal is to preprocess the point set S, such that queries can be answered as effic ..."
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Cited by 138 (9 self)
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. Given any set of n points S ae E d , and a constant ffl ? 0, we produce a data structure, such that given any query point, a point of S will be reported whose distance from the query point is at most a factor of (1 + ffl) from that of the true nearest neighbor. Our algorithm runs in O(log 3 n
A Formal Approach to Recovery by Compensating Transactions
 In Proceedings of the 16th International Conference on Very Large Data Bases
, 1990
"... Compensating transactions are intended to handle situations where it is required to undo either committed or uncommitted transactions that affect other transactions, without resorting to cascading aborts. This stands in sharp contrast to the standard approach to transaction recovery where cascading ..."
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Cited by 171 (5 self)
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Compensating transactions are intended to handle situations where it is required to undo either committed or uncommitted transactions that affect other transactions, without resorting to cascading aborts. This stands in sharp contrast to the standard approach to transaction recovery where cascading aborts are avoided by requiring transactions to read only committed data, and where committed transactions are treated as permanent and irreversible. We argue that this standard approach to recovery is not suitable for a wide range of advanced database applications, in particular those applications that incorporate longduration or nested transactions. We show how compensating transactions can be effectively used to handle these types of applications. We present a model that allows the definition of a variety of types of correct compensation. These types of compensation range from traditional undo, at one extreme, to applicationdependent, specialpurpose compensating transactions, ...
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