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On the Coarseness of Bicolored Point Sets
, 2012
"... Let R be a set of red points and B a set of blue points on the plane. In this paper we introduce a new concept, which we call coarseness, for measuring how blended the elements of S = R ∪ B are. For X ⊆ S, let ∇(X) = X ∩ R  − X ∩ B  be the bichromatic discrepancy of X. We say that a partitio ..."
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Cited by 3 (1 self)
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the coarseness of bicolored point sets, and relate it to well blended point sets. In particular, we show combinatorial results on the coarseness of general configurations and give efficient algorithms for computing the coarseness of two specific cases, namely when the set of points is in convex position and when
Spacetime Interest Points
 IN ICCV
, 2003
"... Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatiotemporal domain and show how the resulting features often reflect interesting events that can be use ..."
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Cited by 791 (22 self)
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Local image features or interest points provide compact and abstract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points into the spatiotemporal domain and show how the resulting features often reflect interesting events that can
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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algorithm, and expresses how well a feature can be tracked. As a result, the criterion is optima...
Iterative point matching for registration of freeform curves and surfaces
, 1994
"... A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
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Cited by 659 (7 self)
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correspondences, which reduces the average distance between points in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
OPTICS: Ordering Points To Identify the Clustering Structure
, 1999
"... Cluster analysis is a primary method for database mining. It is either used as a standalone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of ..."
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Cited by 511 (49 self)
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of the wellknown clustering algorithms require input parameters which are hard to determine but have a significant influence on the clustering result. Furthermore, for many realdata sets there does not even exist a global parameter setting for which the result of the clustering algorithm describes
CURE: An Efficient Clustering Algorithm for Large Data sets
 Published in the Proceedings of the ACM SIGMOD Conference
, 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
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Cited by 713 (5 self)
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of random sampling and partitioning. A random sample drawn from the data set is first partitioned and each partition is partially clustered. The partial clusters are then clustered in a second pass to yield the desired clusters. Our experimental results confirm that the quality of clusters produced by CURE
The SimpleScalar tool set, version 2.0
 Computer Architecture News
, 1997
"... This report describes release 2.0 of the SimpleScalar tool set, a suite of free, publicly available simulation tools that offer both detailed and highperformance simulation of modern microprocessors. The new release offers more tools and capabilities, precompiled binaries, cleaner interfaces, bette ..."
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Cited by 1827 (44 self)
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This report describes release 2.0 of the SimpleScalar tool set, a suite of free, publicly available simulation tools that offer both detailed and highperformance simulation of modern microprocessors. The new release offers more tools and capabilities, precompiled binaries, cleaner interfaces
Effects with Random Assignment: Results for Dartmouth Roommates
, 2001
"... This paper uses a unique data set to measure peer effects among college roommates. Freshman year roommates and dormmates are randomly assigned at Dartmouth College. I find that peers have an impact on grade point average and on decisions to join social groups such as fraternities. Residential peer e ..."
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Cited by 523 (6 self)
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This paper uses a unique data set to measure peer effects among college roommates. Freshman year roommates and dormmates are randomly assigned at Dartmouth College. I find that peers have an impact on grade point average and on decisions to join social groups such as fraternities. Residential peer
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 778 (5 self)
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Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NP
Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
 SIAM Journal on Optimization
, 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
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Cited by 557 (12 self)
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to SDP. Next we present an interior point algorithm which converges to the optimal solution in polynomial time. The approach is a direct extension of Ye's projective method for linear programming. We also argue that most known interior point methods for linear programs can be transformed in a
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