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» Modelling Recursive Calls with UML State Diagrams
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132
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ICSE
2000
IEEE-ACM
15 years 7 months ago
Testing levels for object-oriented software
One of the characteristicsof object-oriented software is the complex dependency that may exist between classes due to inheritance, association and aggregation relationships. Hence...
Yvan Labiche, Pascale Thévenod-Fosse, H&eac...
133
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NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 7 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
140
Voted
QEST
2008
IEEE
15 years 10 months ago
Symbolic Magnifying Lens Abstraction in Markov Decision Processes
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
131
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INFOCOM
2007
IEEE
15 years 10 months ago
Performance Evaluation of Loss Networks via Factor Graphs and the Sum-Product Algorithm
— Loss networks provide a powerful tool for the analysis and design of many communication and networking systems. It is well known that a large number of loss networks have produ...
Jian Ni, Sekhar Tatikonda
128
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PAMI
2010
205views more  PAMI 2010»
15 years 2 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille