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ECML
2005
Springer
14 years 1 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...
JASIS
2011
93views more  JASIS 2011»
13 years 2 months ago
Composition of scientific teams and publication productivity at a national science lab
The production of scientific knowledge has evolved from a process of inquiry largely based on the activities of individual scientists to one grounded in the collaborative efforts ...
Besiki Stvilia, Charles C. Hinnant, Katy Schindler...
IJCAI
2001
13 years 9 months ago
Active Learning for Class Probability Estimation and Ranking
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Maytal Saar-Tsechansky, Foster J. Provost
SECON
2007
IEEE
14 years 2 months ago
Two-hop Relaying in Random Networks with Limited Channel State Information
— In this paper we study two-hop cooperative diversity relaying in random wireless networks. In contrast to most work on cooperative diversity relaying where the relay node posit...
Furuzan Atay Onat, Dan Avidor, Sayandev Mukherjee
IPM
2007
86views more  IPM 2007»
13 years 7 months ago
Document concept lattice for text understanding and summarization
We argue that the quality of a summary can be evaluated based on how many concepts in the original document(s) that reserved after summarization. Here, a concept refers to an abst...
Shiren Ye, Tat-Seng Chua, Min-Yen Kan, Long Qiu