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17 years 5 months ago
Markov Random Field Modeling in Computer Vision
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
Stan Z. Li
FOCS
2008
IEEE
16 years 18 days ago
Computing the Tutte Polynomial in Vertex-Exponential Time
The deletion–contraction algorithm is perhaps the most popular method for computing a host of fundamental graph invariants such as the chromatic, flow, and reliability polynomi...
Andreas Björklund, Thore Husfeldt, Petteri Ka...
169
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ATAL
2006
Springer
15 years 10 months ago
Computational mechanism design for multi-sensor information fusion
Conventional information fusion architectures are challenged by developments in sensor networks that allow individually-owned (and thereby selfish) sensors to interact and share d...
Alex Rogers, Rajdeep K. Dash, Nicholas R. Jennings...
EOR
2007
102views more  EOR 2007»
15 years 6 months ago
Sub-stochastic matrix analysis for bounds computation - Theoretical results
Performance evaluation of complex systems is a critical issue and bounds computation provides confidence about service quality, reliability, etc. of such systems. The stochastic ...
Serge Haddad, Patrice Moreaux
DKE
2002
218views more  DKE 2002»
15 years 6 months ago
Computing iceberg concept lattices with T
We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suit...
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas P...