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HPCC
2005
Springer
14 years 4 months ago
A Coarse Grained Parallel Algorithm for Closest Larger Ancestors in Trees with Applications to Single Link Clustering
Hierarchical clustering methods are important in many data mining and pattern recognition tasks. In this paper we present an efficient coarse grained parallel algorithm for Single...
Albert Chan, Chunmei Gao, Andrew Rau-Chaplin
ML
2000
ACM
150views Machine Learning» more  ML 2000»
13 years 10 months ago
Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
Filippo Menczer, Richard K. Belew
IFIP12
2008
14 years 10 days ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
12 years 1 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray