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» Group-theoretic Algorithms for Matrix Multiplication
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FOGA
2011
14 years 3 months ago
The logarithmic hypervolume indicator
It was recently proven that sets of points maximizing the hypervolume indicator do not give a good multiplicative approximation of the Pareto front. We introduce a new “logarith...
Tobias Friedrich, Karl Bringmann, Thomas Voß...
ICA
2004
Springer
15 years 5 months ago
Approximate Joint Diagonalization Using a Natural Gradient Approach
We present a new algorithm for non-unitary approximate joint diagonalization (AJD), based on a “natural gradient”-type multiplicative update of the diagonalizing matrix, comple...
Arie Yeredor, Andreas Ziehe, Klaus-Robert Mül...
ICDM
2006
IEEE
130views Data Mining» more  ICDM 2006»
15 years 5 months ago
Boosting for Learning Multiple Classes with Imbalanced Class Distribution
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Yanmin Sun, Mohamed S. Kamel, Yang Wang 0007
KDD
2005
ACM
165views Data Mining» more  KDD 2005»
16 years 5 days ago
Co-clustering by block value decomposition
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
ICPR
2002
IEEE
16 years 26 days ago
Data Clustering Using Evidence Accumulation
We explore the idea of evidence accumulation for combining the results of multiple clusterings. Initially, n d-dimensional data is decomposed into a large number of compact cluste...
Ana L. N. Fred, Anil K. Jain