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» Markov Approximation for Combinatorial Network Optimization
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ICML
2004
IEEE
14 years 6 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
INFOCOM
2012
IEEE
11 years 7 months ago
Combinatorial auction with time-frequency flexibility in cognitive radio networks
—In this paper, we tackle the spectrum allocation problem in cognitive radio (CR) networks with time-frequency flexibility consideration using combinatorial auction. Different f...
Mo Dong, Gaofei Sun, Xinbing Wang, Qian Zhang
ALMOB
2006
138views more  ALMOB 2006»
13 years 5 months ago
A combinatorial optimization approach for diverse motif finding applications
Background: Discovering approximately repeated patterns, or motifs, in biological sequences is an important and widely-studied problem in computational molecular biology. Most fre...
Elena Zaslavsky, Mona Singh
PAMI
2007
176views more  PAMI 2007»
13 years 4 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
ECAI
2008
Springer
13 years 7 months ago
Structure Learning of Markov Logic Networks through Iterated Local Search
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
Marenglen Biba, Stefano Ferilli, Floriana Esposito