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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
15 years 10 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
ICC
2007
IEEE
115views Communications» more  ICC 2007»
15 years 4 months ago
Distributed Minimum-Cost Clustering Protocol for UnderWater Sensor Networks (UWSNs)
—In this paper, we study the node clustering problem in UnderWater Sensor Networks (UWSNs). We formulate the problem into a cluster-centric cost-based optimization problem with a...
Pu Wang, Cheng Li, Jun Zheng
124
Voted
ROBOCUP
2004
Springer
288views Robotics» more  ROBOCUP 2004»
15 years 3 months ago
Motion Detection and Tracking for an AIBO Robot Using Camera Motion Compensation and Kalman Filtering
Motion detection and tracking while moving is a desired ability for any soccer player. For instance, this ability allows the determination of the ball trajectory when the player is...
Javier Ruiz-del-Solar, Paul A. Vallejos
ECML
2004
Springer
15 years 3 months ago
Associative Clustering
This report contains derivations which did not fit into the paper [3]. Associative clustering (AC) is a method for separately clustering two data sets when one-to-one association...
Janne Sinkkonen, Janne Nikkilä, Leo Lahti, Sa...
93
Voted
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
15 years 10 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney