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The Nature of Statistical Learning Theory
, 1999
"... Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based on the deve ..."
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Cited by 13236 (32 self)
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Statistical learning theory was introduced in the late 1960’s. Until the 1990’s it was a purely theoretical analysis of the problem of function estimation from a given collection of data. In the middle of the 1990’s new types of learning algorithms (called support vector machines) based
Algorithms for the Data Placement Problem
"... 1 Introduction We consider the data placement problem introduced by Baev & Rajaraman [1]. We have a set of caches, F, a set of data objects O, and a set of clients D. Each object s 2 O has a length ls and a cache i 2 Fhas capacity ui that limits the total length of data objects that may be store ..."
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1 Introduction We consider the data placement problem introduced by Baev & Rajaraman [1]. We have a set of caches, F, a set of data objects O, and a set of clients D. Each object s 2 O has a length ls and a cache i 2 Fhas capacity ui that limits the total length of data objects that may
Improved Algorithms for the Data Placement Problem
 Proceedings of the 13th ACMSIAM Symposium on Discrete Algorithms
, 2002
"... Introduction We study the data placement problem [1, 3], where the goal is to place data objects in xed capacity caches in a network to optimize latency of access. Each user has a demand for a specic object. The latencies on the network are modeled by a metric distance. Each cache can store a certa ..."
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Cited by 12 (1 self)
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Introduction We study the data placement problem [1, 3], where the goal is to place data objects in xed capacity caches in a network to optimize latency of access. Each user has a demand for a specic object. The latencies on the network are modeled by a metric distance. Each cache can store a
1 Introduction Algorithms for the Data Placement Problem
"... We consider the data placement problem introduced by Baev & Rajaraman [1]. We have a set of caches, F, a set of data objects O, and a set of clients D. Each object s ∈ O has a length ls and a cache i ∈ F ..."
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We consider the data placement problem introduced by Baev & Rajaraman [1]. We have a set of caches, F, a set of data objects O, and a set of clients D. Each object s ∈ O has a length ls and a cache i ∈ F
Dryad: Distributed DataParallel Programs from Sequential Building Blocks
 In EuroSys
, 2007
"... Dryad is a generalpurpose distributed execution engine for coarsegrain dataparallel applications. A Dryad application combines computational “vertices ” with communication “channels ” to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of availa ..."
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Cited by 762 (27 self)
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simultaneously on multiple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation progresses to make efficient use of the available resources. Dryad is designed to scale from powerful multicore sin
Data Security
, 1979
"... The rising abuse of computers and increasing threat to personal privacy through data banks have stimulated much interest m the techmcal safeguards for data. There are four kinds of safeguards, each related to but distract from the others. Access controls regulate which users may enter the system and ..."
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Cited by 615 (3 self)
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The rising abuse of computers and increasing threat to personal privacy through data banks have stimulated much interest m the techmcal safeguards for data. There are four kinds of safeguards, each related to but distract from the others. Access controls regulate which users may enter the system
Data Integration: A Theoretical Perspective
 Symposium on Principles of Database Systems
, 2002
"... Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues that are interestin ..."
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Cited by 965 (45 self)
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Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
, 2003
"... One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a lowdimensional manifold embedded in a highdimensional space. Drawing on the correspondenc ..."
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Cited by 1226 (15 self)
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One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a lowdimensional manifold embedded in a highdimensional space. Drawing
A new approach to the maximum flow problem
 JOURNAL OF THE ACM
, 1988
"... All previously known efficient maximumflow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortestlength augmenting paths at once (using the layered network approach of Dinic). An alternative method based on the pre ..."
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Cited by 672 (33 self)
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to be shortest paths. The algorithm and its analysis are simple and intuitive, yet the algorithm runs as fast as any other known method on dense. graphs, achieving an O(n³) time bound on an nvertex graph. By incorporating the dynamic tree data structure of Sleator and Tarjan, we obtain a version
The Xtree: An index structure for highdimensional data
 In Proceedings of the Int’l Conference on Very Large Data Bases
, 1996
"... In this paper, we propose a new method for indexing large amounts of point and spatial data in highdimensional space. An analysis shows that index structures such as the R*tree are not adequate for indexing highdimensional data sets. The major problem of Rtreebased index structures is the over ..."
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Cited by 592 (17 self)
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In this paper, we propose a new method for indexing large amounts of point and spatial data in highdimensional space. An analysis shows that index structures such as the R*tree are not adequate for indexing highdimensional data sets. The major problem of Rtreebased index structures
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