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» Learning to generalize for complex selection tasks
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IUI
2004
ACM
14 years 1 months ago
An intelligent assistant for interactive workflow composition
Complex applications in many areas, including scientific computations and business-related web services, are created from collections of components to form workflows. In many case...
Jihie Kim, Marc Spraragen, Yolanda Gil
HPDC
1999
IEEE
13 years 12 months ago
Remote Application Scheduling on Metacomputing Systems
Efficient and robust metacomputing requires the decomposition of complex jobs into tasks that must be scheduled on distributed processing nodes. There are various ways of creating...
Heath A. James, Kenneth A. Hawick
CIKM
2006
Springer
13 years 11 months ago
Finding highly correlated pairs efficiently with powerful pruning
We consider the problem of finding highly correlated pairs in a large data set. That is, given a threshold not too small, we wish to report all the pairs of items (or binary attri...
Jian Zhang, Joan Feigenbaum
BCSHCI
2008
13 years 9 months ago
Low cost prototyping: part 2, or how to apply the thinking-aloud method efficiently
Customer satisfaction with regard to user interfaces becomes increasingly more important and is, eventually, decisive for the selection of systems within a competitive market. End...
Andreas Holzinger, Stephen Brown
JACM
2006
99views more  JACM 2006»
13 years 7 months ago
Finding a maximum likelihood tree is hard
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
Benny Chor, Tamir Tuller