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» A Partial-Repeatability Approach to Data Mining
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SDM
2012
SIAM
261views Data Mining» more  SDM 2012»
13 years 6 months ago
Combining Active Learning and Dynamic Dimensionality Reduction
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
Mustafa Bilgic
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 5 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
15 years 11 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard
ICDM
2009
IEEE
205views Data Mining» more  ICDM 2009»
15 years 11 months ago
Active Selection of Sensor Sites in Remote Sensing Applications
— In a data-mining approach, a model for estimation of Aerosol Optical Depth (AOD) from satellite observations is learned using collocated satellite and groundbased observations....
Debasish Das, Zoran Obradovic, Slobodan Vucetic
ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
15 years 10 months ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan