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103
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CIKM
1997
Springer
15 years 4 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
119
Voted
IDA
2009
Springer
14 years 10 months ago
Context-Based Distance Learning for Categorical Data Clustering
Abstract. Clustering data described by categorical attributes is a challenging task in data mining applications. Unlike numerical attributes, it is difficult to define a distance b...
Dino Ienco, Ruggero G. Pensa, Rosa Meo
96
Voted
IJCAI
2003
15 years 1 months ago
A Learning Algorithm for Localizing People Based on Wireless Signal Strength that Uses Labeled and Unlabeled Data
This paper summarizes a probabilistic approach for localizing people through the signal strengths of a wireless IEEE 802.11b network. Our approach uses data labeled by ground trut...
Sebastian Thrun, Geoffrey J. Gordon, Frank Pfennin...
DAC
2011
ACM
14 years 8 days ago
AENEID: a generic lithography-friendly detailed router based on post-RET data learning and hotspot detection
In the era of deep sub-wavelength lithography for nanometer VLSI designs, manufacturability and yield issues are critical and need to be addressed during the key physical design i...
Duo Ding, Jhih-Rong Gao, Kun Yuan, David Z. Pan
121
Voted
CVPR
2004
IEEE
16 years 2 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...