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IWPEC
2010
Springer
15 years 4 months ago
Partial Kernelization for Rank Aggregation: Theory and Experiments
RANK AGGREGATION is important in many areas ranging from web search over databases to bioinformatics. The underlying decision problem KEMENY SCORE is NP-complete even in case of fo...
Nadja Betzler, Robert Bredereck, Rolf Niedermeier
ACL
2009
15 years 4 months ago
K-Best A* Parsing
A parsing makes 1-best search efficient by suppressing unlikely 1-best items. Existing kbest extraction methods can efficiently search for top derivations, but only after an exhau...
Adam Pauls, Dan Klein
ICASSP
2011
IEEE
14 years 10 months ago
Feature selection through gravitational search algorithm
In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimi...
João Paulo Papa, Andre Pagnin, Silvana Arti...
AAAI
2012
13 years 8 months ago
Sequential Decision Making with Rank Dependent Utility: A Minimax Regret Approach
This paper is devoted to sequential decision making with Rank Dependent expected Utility (RDU). This decision criterion generalizes Expected Utility and enables to model a wider r...
Gildas Jeantet, Patrice Perny, Olivier Spanjaard
ESA
2009
Springer
346views Algorithms» more  ESA 2009»
16 years 25 days ago
Hash, Displace, and Compress
A hash function h, i.e., a function from the set U of all keys to the range range [m] = {0, . . . , m − 1} is called a perfect hash function (PHF) for a subset S ⊆ U of size n ...
Djamal Belazzougui, Fabiano C. Botelho, Martin Die...