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» Active Learning for Networked Data
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140
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JMLR
2006
140views more  JMLR 2006»
15 years 2 months ago
Active Learning in Approximately Linear Regression Based on Conditional Expectation of Generalization Error
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Masashi Sugiyama
124
Voted
HPDC
2005
IEEE
15 years 8 months ago
Lerna: an active storage framework for flexible data access and management
In the present paper, we examine the problem of supporting application-specific computation within a network file server. Our objectives are (i) to introduce an easy to use yet ...
Stergios V. Anastasiadis, Rajiv Wickremesinghe, Je...
248
Voted
PAKDD
2011
ACM
473views Data Mining» more  PAKDD 2011»
14 years 8 months ago
 Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy Hospedales, Shaogang Gong and Tao Xiang
IJCAI
1997
15 years 4 months ago
An Effective Learning Method for Max-Min Neural Networks
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
Loo-Nin Teow, Kia-Fock Loe
132
Voted
SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
15 years 12 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh