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NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 11 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
STOC
1996
ACM
92views Algorithms» more  STOC 1996»
13 years 11 months ago
Constructing Evolutionary Trees in the Presence of Polymorphic Characters
Abstract. Most phylogenetics literature and construction methods based upon characters presume monomorphism (one state per character per species), yet polymorphism (multiple states...
Maria Luisa Bonet, Cynthia A. Phillips, Tandy Warn...
CONEXT
2007
ACM
13 years 11 months ago
Internet routing resilience to failures: analysis and implications
Internet interdomain routing is policy-driven, and thus physical connectivity does not imply reachability. On average, routing on today's Internet works quite well, ensuring ...
Jian Wu, Ying Zhang, Zhuoqing Morley Mao, Kang G. ...
CVPR
2004
IEEE
13 years 11 months ago
Efficient Graphical Models for Processing Images
Graphical models are powerful tools for processing images. However, the large dimensionality of even local image data poses a difficulty: representing the range of possible graphi...
Marshall F. Tappen, Bryan C. Russell, William T. F...
VISUAL
2000
Springer
13 years 11 months ago
Statistical Motion-Based Retrieval with Partial Query
We present an original approach for motion-based retrieval involving partial query. More precisely, we propose an uni ed statistical framework both to extract entities of interest ...
Ronan Fablet, Patrick Bouthemy