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» Using Data Mining to Estimate Missing Sensor Data
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ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 11 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
ICASSP
2011
IEEE
14 years 9 months ago
Robust hyperspectral signal unmixing in the presence of correlated noise
Hyperspectral imaging analysis aims at the estimation of the number of constituent substances, known as endmembers, their spectral signatures as well as their abundance fractions ...
Masoud Farzam, Soosan Beheshti
VLDB
2007
ACM
141views Database» more  VLDB 2007»
16 years 6 months ago
Query Processing over Incomplete Autonomous Databases
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous web databases, on which user accesses are usually supported through media...
Garrett Wolf, Hemal Khatri, Bhaumik Chokshi, Jianc...
PERCOM
2005
ACM
16 years 5 months ago
Adaptive Temporal Radio Maps for Indoor Location Estimation
In this paper, we present a novel method to adapt the temporal radio maps for indoor location determination by offsetting the variational environmental factors using data mining t...
Jie Yin, Qiang Yang, Lionel M. Ni
GFKL
2007
Springer
184views Data Mining» more  GFKL 2007»
16 years 5 days ago
A Probabilistic Relational Model for Characterizing Situations in Dynamic Multi-Agent Systems
Abstract. Artificial systems with a high degree of autonomy require reliable semantic information about the context they operate in. State interpretation, however, is a difficult ...
Daniel Meyer-Delius, Christian Plagemann, Georg vo...