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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 11 months ago
Improving data mining utility with projective sampling
Overall performance of the data mining process depends not just on the value of the induced knowledge but also on various costs of the process itself such as the cost of acquiring...
Mark Last
ATAL
2010
Springer
15 years 8 months ago
Planning against fictitious players in repeated normal form games
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
Enrique Munoz de Cote, Nicholas R. Jennings
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 8 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
BMCBI
2008
153views more  BMCBI 2008»
15 years 7 months ago
Improved general regression network for protein domain boundary prediction
Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary ...
Paul D. Yoo, Abdur R. Sikder, Bing Bing Zhou, Albe...
VL
2009
IEEE
156views Visual Languages» more  VL 2009»
16 years 1 months ago
Non-programmers identifying functionality in unfamiliar code: Strategies and barriers
Source code on the web is a widely available and potentially rich learning resource for nonprogrammers. However, unfamiliar code can be daunting to end-users without programming e...
Paul A. Gross, Caitlin Kelleher
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