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PRL
2006
139views more  PRL 2006»
13 years 4 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...
ICRA
2005
IEEE
139views Robotics» more  ICRA 2005»
13 years 10 months ago
Making Collective Behaviours to work through Implicit Communication
— The aim of this paper is to investigate how stigmergic information allow each individual of a group of autonomous robots to take advantages from other individual behaviors. The...
Antonio D'Angelo, Enrico Pagello
ECAL
2005
Springer
13 years 10 months ago
On Convergence of Dynamic Cluster Formation in Multi-agent Networks
Efficient hierarchical architectures for reconfigurable and adaptive multi-agent networks require dynamic cluster formation among the set of nodes (agents). In the absence of cen...
Mikhail Prokopenko, Piraveenan Mahendra rajah, Pet...
ACSC
2007
IEEE
13 years 11 months ago
Dynamic Measurement of Polymorphism
Measuring "reuse" and "reusability" is difficult because there are so many different facets to these concepts. Before we can effectively measure reuse and reus...
Kelvin Choi, Ewan D. Tempero
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
13 years 11 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof