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» The Kernel Least-Mean-Square Algorithm
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218
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ICDM
2006
IEEE
139views Data Mining» more  ICDM 2006»
15 years 9 months ago
Unsupervised Clustering In Streaming Data
Tools for automatically clustering streaming data are becoming increasingly important as data acquisition technology continues to advance. In this paper we present an extension of...
Dimitris K. Tasoulis, Niall M. Adams, David J. Han...
119
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FCCM
2005
IEEE
106views VLSI» more  FCCM 2005»
15 years 9 months ago
High-Performance FPGA-Based General Reduction Methods
FPGA-based floating-point kernels must exploit algorithmic parallelism and use deeply pipelined cores to gain a performance advantage over general-purpose processors. Inability t...
Gerald R. Morris, Ling Zhuo, Viktor K. Prasanna
120
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ISNN
2005
Springer
15 years 9 months ago
Multiple Parameter Selection for LS-SVM Using Smooth Leave-One-Out Error
In least squares support vector (LS-SVM), the key challenge lies in the selection of free parameters such as kernel parameters and tradeoff parameter. However, when a large number ...
Liefeng Bo, Ling Wang, Licheng Jiao
129
Voted
ICMLA
2008
15 years 5 months ago
An Improved Generalized Discriminant Analysis for Large-Scale Data Set
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue
136
Voted
NIPS
2004
15 years 5 months ago
Supervised Graph Inference
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...
Jean-Philippe Vert, Yoshihiro Yamanishi