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Data partition

by James R. Leavitt A, Kevin D. Hiatt A, Michael F. Whiting A, Hojun Song A , 2012
"... This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or sel ..."
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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit:

Data Partitioning for Reconfigurable Architectures with

by Wenrui Gong, Yan Meng, Gang Wang, Ryan Kastner - Distributed Block RAM” – International Workshop on Logic and Synthesis (IWLS , 2005
"... Contemporary reconfigurable architectures integrate distributed block RAM modules on-chip to provide ample storage for DSP, wireless, and image processing applications. Synthesizing applications to these complex systems requires an effective and efficient approach to conduct data partitioning and st ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Contemporary reconfigurable architectures integrate distributed block RAM modules on-chip to provide ample storage for DSP, wireless, and image processing applications. Synthesizing applications to these complex systems requires an effective and efficient approach to conduct data partitioning

Maximum Certainty Data Partitioning

by Stephen J. Roberts, Richard Everson, Iead Rezek , 1999
"... Problems in data analysis often require the unsupervised partitioning of a data set into clusters. Many methods exist for such partitioning but most have the weakness of being model-based (most assuming hyper-ellipsoidal clusters) or computationally infeasible in anything more than a 3-dimensional d ..."
Abstract - Cited by 17 (0 self) - Add to MetaCart
Problems in data analysis often require the unsupervised partitioning of a data set into clusters. Many methods exist for such partitioning but most have the weakness of being model-based (most assuming hyper-ellipsoidal clusters) or computationally infeasible in anything more than a 3-dimensional

A Linear-Time Heuristic for Improving Network Partitions

by C. M. Fiduccia, et al. , 1982
"... An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To d ..."
Abstract - Cited by 524 (0 self) - Add to MetaCart
. To deal with cells of various sizes, the algorithm progresses by moving one cell at a time between the blocks of the partition while maintaining a desired balance based on the size of the blocks rather than the number of cells per block. Efficient data structures are used to avoid unnecessary searching

Error Concealment by Data Partitioning

by Raj Talluri, Iole Moccagatta, Yashoda Nag, Gene Cheung - Signal Process.: Image Commun , 1997
"... This paper presents an error concealment strategy for improving the quality of compressed video data when transmitted over noisy communication channels. Data partitioning is used to enable the recovery of motion information when the compressed bitstream is corrupted by channels errors. At low bitrat ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
This paper presents an error concealment strategy for improving the quality of compressed video data when transmitted over noisy communication channels. Data partitioning is used to enable the recovery of motion information when the compressed bitstream is corrupted by channels errors. At low

Finding Consistent Clusters in Data Partitions

by Ana Fred - IN PROC. 3D INT. WORKSHOP ON MULTIPLE CLASSIFIER , 2001
"... Given an arbitrary data set, to which no particular parametrical, statistical or geometrical structure can be assumed, different clustering algorithms will in general produce different data partitions. In fact, several partitions can also be obtained by using a single clustering algorithm due to d ..."
Abstract - Cited by 55 (6 self) - Add to MetaCart
Given an arbitrary data set, to which no particular parametrical, statistical or geometrical structure can be assumed, different clustering algorithms will in general produce different data partitions. In fact, several partitions can also be obtained by using a single clustering algorithm due

Cluster Ensembles - A Knowledge Reuse Framework for Combining Multiple Partitions

by Alexander Strehl, Joydeep Ghosh, Claire Cardie - Journal of Machine Learning Research , 2002
"... This paper introduces the problem of combining multiple partitionings of a set of objects into a single consolidated clustering without accessing the features or algorithms that determined these partitionings. We first identify several application scenarios for the resultant 'knowledge reuse&ap ..."
Abstract - Cited by 603 (20 self) - Add to MetaCart
This paper introduces the problem of combining multiple partitionings of a set of objects into a single consolidated clustering without accessing the features or algorithms that determined these partitionings. We first identify several application scenarios for the resultant 'knowledge reuse

Automatic Data Partitioning on Distributed Memory Multiprocessors

by Manish Gupta, Prithviraj Banerjee , 1991
"... An important problem facing numerous research projects on parallelizing compilers for distributed memory machines is that of automatically determining a suitable data partitioning scheme for a program. Most of the current projects leave this tedious problem almost entirely to the user. In this paper ..."
Abstract - Cited by 108 (6 self) - Add to MetaCart
An important problem facing numerous research projects on parallelizing compilers for distributed memory machines is that of automatically determining a suitable data partitioning scheme for a program. Most of the current projects leave this tedious problem almost entirely to the user

Data Partitioning on Chip Multiprocessors

by John Cieslewicz, Kenneth A. Ross
"... Partitioning is a key database task. In this paper we explore partitioning performance on a chip multiprocessor (CMP) that provides a relatively high degree of on-chip thread-level parallelism. It is therefore important to implement the partitioning algorithm to take advantage of the CMP’s parallel ..."
Abstract - Cited by 15 (3 self) - Add to MetaCart
Partitioning is a key database task. In this paper we explore partitioning performance on a chip multiprocessor (CMP) that provides a relatively high degree of on-chip thread-level parallelism. It is therefore important to implement the partitioning algorithm to take advantage of the CMP’s parallel

Minimum Entropy Data Partitioning

by Stephen J. Roberts, Richard Everson, Iead Rezek - in Proceedings of International Conference on Artificial Neural Networks , 1999
"... Problems in data analysis often require the unsupervised partitioning of a data set into clusters. Many methods exist for such partitioning but most have the weakness of being model-based (most assuming hyper-ellipsoidal clusters) or computationally infeasible in anything more than a 3dimensional da ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
Problems in data analysis often require the unsupervised partitioning of a data set into clusters. Many methods exist for such partitioning but most have the weakness of being model-based (most assuming hyper-ellipsoidal clusters) or computationally infeasible in anything more than a 3dimensional
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Results 1 - 10 of 13,253
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