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» Approximation Algorithms for Clustering Problems
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IS
2007
15 years 6 months ago
Mining association rules in very large clustered domains
Emerging applications introduce the requirement for novel association-rule mining algorithms that will be scalable not only with respect to the number of records (number of rows) ...
Alexandros Nanopoulos, Apostolos N. Papadopoulos, ...
CVPR
2006
IEEE
16 years 26 days ago
Nonlinear Mean Shift for Clustering over Analytic Manifolds
The mean shift algorithm is widely applied for nonparametric clustering in Euclidean spaces. Recently, mean shift was generalized for clustering on matrix Lie groups. We further e...
Raghav Subbarao, Peter Meer
ATAL
2007
Springer
16 years 1 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa
KDD
2001
ACM
196views Data Mining» more  KDD 2001»
16 years 7 months ago
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifie...
Cheng Yang, Usama M. Fayyad, Paul S. Bradley
162
Voted
SODA
2001
ACM
102views Algorithms» more  SODA 2001»
15 years 8 months ago
Approximate majorization and fair online load balancing
This paper relates the notion of fairness in online routing and load balancing to vector majorization as developed by Hardy, Littlewood, and Polya 9]. We de ne -supermajorization ...
Ashish Goel, Adam Meyerson, Serge A. Plotkin