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» A Use Case Based Approach to Feature Models' Construction
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SIGIR
2008
ACM
14 years 11 months ago
Directly optimizing evaluation measures in learning to rank
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma
POPL
2009
ACM
16 years 12 days ago
A cost semantics for self-adjusting computation
Self-adjusting computation is an evaluation model in which programs can respond efficiently to small changes to their input data by using a change-propagation mechanism that updat...
Ruy Ley-Wild, Umut A. Acar, Matthew Fluet
PLDI
2010
ACM
15 years 4 months ago
Traceable data types for self-adjusting computation
Self-adjusting computation provides an evaluation model where computations can respond automatically to modifications to their data by using a mechanism for propagating modifica...
Umut A. Acar, Guy E. Blelloch, Ruy Ley-Wild, Kanat...
ICFP
2009
ACM
16 years 12 days ago
Causal commutative arrows and their optimization
re a popular form of abstract computation. Being more general than monads, they are more broadly applicable, and in parare a good abstraction for signal processing and dataflow co...
Hai Liu, Eric Cheng, Paul Hudak
ICFP
2003
ACM
15 years 11 months ago
Dynamic rebinding for marshalling and update, with destruct-time?
Most programming languages adopt static binding, but for distributed programming an exclusive reliance on static binding is too restrictive: dynamic binding is required in various...
Gavin M. Bierman, Michael W. Hicks, Peter Sewell, ...