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» Learning Rules from Distributed Data
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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 6 days ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
ASC
2011
14 years 6 months ago
Handling drifts and shifts in on-line data streams with evolving fuzzy systems
In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact tha...
Edwin Lughofer, Plamen P. Angelov
AAAI
2010
14 years 9 months ago
A Topic Model for Linked Documents and Update Rules for its Estimation
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Zhen Guo, Shenghuo Zhu, Zhongfei Zhang, Yun Chi, Y...
IFIP
2007
Springer
15 years 6 months ago
Lessons Learned from the Maroochy Water Breach
Supervisory control and data acquisition (SCADA) systems are widely used to monitor and control operations in electrical power distribution facilities, oil and gas pipelines, water...
Jill Slay, Michael Miller
ICML
1999
IEEE
16 years 18 days ago
Abstracting from Robot Sensor Data using Hidden Markov Models
ing from Robot Sensor Data using Hidden Markov Models Laura Firoiu, Paul Cohen Computer Science Department, LGRC University of Massachusetts at Amherst, Box 34610 Amherst, MA 01003...
Laura Firoiu, Paul R. Cohen