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ICAI
2007
14 years 11 months ago
Dynamic Programming Algorithm for Training Functional Networks
Abstract— The paper proposes a dynamic programming algorithm for training of functional networks. The algorithm considers each node as a state. The problem is formulated as find...
Emad A. El-Sebakhy, Salahadin Mohammed, Moustafa E...
92
Voted
AIEDAM
2008
127views more  AIEDAM 2008»
14 years 10 months ago
Evolving blackbox quantum algorithms using genetic programming
Although it is known that quantum computers can solve certain computational problems exponentially faster than classical computers, only a small number of quantum algorithms have ...
Ralf Stadelhofer, Wolfgang Banzhaf, Dieter Suter
92
Voted
JMLR
2010
118views more  JMLR 2010»
14 years 4 months ago
Exploiting Within-Clique Factorizations in Junction-Tree Algorithms
It is probably fair to say that exact inference in graphical models is considered a solved problem, at least regarding its computational complexity: it is exponential in the treew...
Julian John McAuley, Tibério S. Caetano
GD
2005
Springer
15 years 3 months ago
Applications of Parameterized st-Orientations in Graph Drawing Algorithms
Abstract. Many graph drawing algorithms use st-numberings (st-orientations or bipolar orientations) as a first step. An st-numbering of a biconnected undirected graph defines a d...
Charalampos Papamanthou, Ioannis G. Tollis
ICML
2005
IEEE
15 years 11 months ago
Expectation maximization algorithms for conditional likelihoods
We introduce an expectation maximizationtype (EM) algorithm for maximum likelihood optimization of conditional densities. It is applicable to hidden variable models where the dist...
Jarkko Salojärvi, Kai Puolamäki, Samuel ...