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KDD
2005
ACM
135views Data Mining» more  KDD 2005»
16 years 4 months ago
A hybrid unsupervised approach for document clustering
We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Mihai Surdeanu, Jordi Turmo, Alicia Ageno
165
Voted
IAT
2009
IEEE
15 years 11 months ago
Cluster-Swap: A Distributed K-median Algorithm for Sensor Networks
In building practical sensor networks, it is often beneficial to use only a subset of sensors to take measurements because of computational, communication, and power limitations....
Yoonheui Kim, Victor R. Lesser, Deepak Ganesan, Ra...
PAMI
2006
134views more  PAMI 2006»
15 years 4 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Michael Laszlo, Sumitra Mukherjee
ICCAD
2004
IEEE
83views Hardware» more  ICCAD 2004»
16 years 1 months ago
Custom-optimized multiplierless implementations of DSP algorithms
Linear DSP kernels such as transforms and filters are comprised exclusively of additions and multiplications by constants. These multiplications may be realized as networks of ad...
Markus Püschel, Adam C. Zelinski, James C. Ho...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 10 months ago
Greedy, genetic, and greedy genetic algorithms for the quadratic knapsack problem
Augmenting an evolutionary algorithm with knowledge of its target problem can yield a more effective algorithm, as this presentation illustrates. The Quadratic Knapsack Problem e...
Bryant A. Julstrom