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ICFCA
2009
Springer
16 years 28 days ago
Factor Analysis of Incidence Data via Novel Decomposition of Matrices
Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidd...
Radim Belohlávek, Vilém Vychodil
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
16 years 21 days ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
ICPR
2004
IEEE
16 years 7 months ago
Landscape of Clustering Algorithms
Numerous clustering algorithms, their taxonomies and evaluation studies are available in the literature. Despite the diversity of different clustering algorithms, solutions delive...
Anil K. Jain, Alexander P. Topchy, Martin H. C. La...
GECCO
2009
Springer
167views Optimization» more  GECCO 2009»
16 years 21 days ago
Fixed-parameter evolutionary algorithms and the vertex cover problem
In this paper, we consider multi-objective evolutionary algorithms for the Vertex Cover problem in the context of parameterized complexity. We relate the runtime of our algorithms...
Stefan Kratsch, Frank Neumann
WAOA
2007
Springer
158views Algorithms» more  WAOA 2007»
16 years 7 days ago
Deterministic Algorithms for Rank Aggregation and Other Ranking and Clustering Problems
We consider ranking and clustering problems related to the aggregation of inconsistent information. Ailon, Charikar, and Newman [1] proposed randomized constant factor approximatio...
Anke van Zuylen, David P. Williamson