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ICDE
2009
IEEE
151views Database» more  ICDE 2009»
14 years 11 months ago
Decision Trees for Uncertain Data
Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information, which originates from...
Smith Tsang, Ben Kao, Kevin Y. Yip, Wai-Shing Ho, ...
NIPS
2003
13 years 11 months ago
Semi-Supervised Learning with Trees
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...
ISAAC
2007
Springer
70views Algorithms» more  ISAAC 2007»
14 years 4 months ago
Kinetic Maintenance of Mobile k-Centres on Trees
Let C denote a set of n mobile clients, each of which follows a continuous trajectory on a weighted tree T. We establish tight bounds on the maximum relative velocity of the 1-cent...
Stephane Durocher, Christophe Paul
ICDM
2003
IEEE
92views Data Mining» more  ICDM 2003»
14 years 3 months ago
Postprocessing Decision Trees to Extract Actionable Knowledge
Most data mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques, when applied to industrial pro...
Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen
FUIN
2010
143views more  FUIN 2010»
13 years 7 months ago
Cluster Tree Elimination for Distributed Constraint Optimization with Quality Guarantees
Some distributed constraint optimization algorithms use a linear number of messages in the number of agents, but of exponential size. This is often the main limitation for their pr...
Ismel Brito, Pedro Meseguer