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ICML
2007
IEEE
16 years 4 months ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu
UCS
2007
Springer
15 years 10 months ago
The iNAV Indoor Navigation System
COMPASS is a location framework where location sources are realized as plugins that contribute probability density functions to the overall localization result. In addition, COMPAS...
Frank Kargl, Sascha Geßler, Florian Flerlage
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
15 years 5 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
ICCV
2005
IEEE
16 years 5 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ICPADS
1996
IEEE
15 years 8 months ago
Implementation of MAP: A system for mobile assistant programming
We have de ne a network programming model called Mobile Assistant Programming (MAP) for development and execution of communication applications in large scale networks of heteroge...
Stéphane Perret, Andrzej Duda