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DAGM
2008
Springer
13 years 6 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
CLOUDCOM
2010
Springer
13 years 2 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin
IPPS
2005
IEEE
13 years 10 months ago
Improvement of Power-Performance Efficiency for High-End Computing
Left unchecked, the fundamental drive to increase peak performance using tens of thousands of power hungry components will lead to intolerable operating costs and failure rates. R...
Rong Ge, Xizhou Feng, Kirk W. Cameron
NIPS
2008
13 years 6 months ago
Counting Solution Clusters in Graph Coloring Problems Using Belief Propagation
We show that an important and computationally challenging solution space feature of the graph coloring problem (COL), namely the number of clusters of solutions, can be accurately...
Lukas Kroc, Ashish Sabharwal, Bart Selman
IPPS
2010
IEEE
13 years 2 months ago
Large-scale multi-dimensional document clustering on GPU clusters
Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulat...
Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas...