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ECML
2005
Springer
14 years 3 months ago
Active Learning for Probability Estimation Using Jensen-Shannon Divergence
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
CIKM
2010
Springer
13 years 8 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang
NIPS
2007
13 years 11 months ago
Selecting Observations against Adversarial Objectives
In many applications, one has to actively select among a set of expensive observations before making an informed decision. Often, we want to select observations which perform well...
Andreas Krause, H. Brendan McMahan, Carlos Guestri...
SIGMOD
2010
ACM
213views Database» more  SIGMOD 2010»
14 years 2 months ago
On active learning of record matching packages
We consider the problem of learning a record matching package (classifier) in an active learning setting. In active learning, the learning algorithm picks the set of examples to ...
Arvind Arasu, Michaela Götz, Raghav Kaushik
GLOBECOM
2009
IEEE
14 years 4 months ago
Optimal Relay-Subset Selection and Time-Allocation in Decode-and-Forward Cooperative Networks
—We present the optimal relay-subset selection and transmission-time for a decode-and-forward, half-duplex cooperative network of arbitrary size. The resource allocation is obtai...
Elzbieta Beres, Raviraj Adve