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ECCV
2010
Springer
15 years 6 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
JACM
2006
99views more  JACM 2006»
15 years 6 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
RECOMB
2005
Springer
16 years 7 months ago
Rapid Protein Side-Chain Packing via Tree Decomposition
This paper proposes a novel tree decomposition based side-chain assignment algorithm, which can obtain the globally optimal solution of the side-chain packing problem very efficien...
Jinbo Xu
GECCO
2005
Springer
195views Optimization» more  GECCO 2005»
16 years 5 days ago
Evolving fuzzy decision tree structure that adapts in real-time
A fuzzy logic algorithm has been developed that automatically allocates electronic attack (EA) resources distributed over different platforms in real-time. The controller must be ...
James F. Smith III
STOC
1994
ACM
168views Algorithms» more  STOC 1994»
15 years 10 months ago
Fast algorithms for finding randomized strategies in game trees
Interactions among agents can be conveniently described by game trees. In order to analyze a game, it is important to derive optimal (or equilibrium) strategies for the di erent p...
Daphne Koller, Nimrod Megiddo, Bernhard von Stenge...