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ECML
2007
Springer
14 years 1 months ago
Learning Metrics Between Tree Structured Data: Application to Image Recognition
The problem of learning metrics between structured data (strings, trees or graphs) has been the subject of various recent papers. With regard to the specific case of trees, some a...
Laurent Boyer 0002, Amaury Habrard, Marc Sebban
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
CVPR
2007
IEEE
14 years 9 months ago
Learning Motion Categories using both Semantic and Structural Information
Current approaches to motion category recognition typically focus on either full spatiotemporal volume analysis (holistic approach) or analysis of the content of spatiotemporal in...
Shu-Fai Wong, Tae-Kyun Kim, Roberto Cipolla
TSP
2011
197views more  TSP 2011»
13 years 2 months ago
Group Object Structure and State Estimation With Evolving Networks and Monte Carlo Methods
—This paper proposes a technique for motion estimation of groups of targets based on evolving graph networks. The main novelty over alternative group tracking techniques stems fr...
Amadou Gning, Lyudmila Mihaylova, Simon Maskell, S...
JMLR
2006
113views more  JMLR 2006»
13 years 7 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...