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» The Probabilistic Method
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122
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ICRA
2009
IEEE
207views Robotics» more  ICRA 2009»
14 years 10 months ago
Bayesian network-based behavior control for skilligent robots
A Skilligent robot must be able to learn skills autonomously to accomplish a task. "Skilligence" is the capacity of the robot to control behaviors reasonably, based on th...
Sang Hyoung Lee, Il Hong Suh
101
Voted
SFM
2007
Springer
15 years 7 months ago
Tackling Large State Spaces in Performance Modelling
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...
William J. Knottenbelt, Jeremy T. Bradley
117
Voted
JSS
2007
109views more  JSS 2007»
15 years 10 days ago
Using Bayesian belief networks for change impact analysis in architecture design
Research into design rationale in the past has focused on argumentation-based design deliberations. These approaches cannot be used to support change impact analysis effectively ...
Antony Tang, Ann E. Nicholson, Yan Jin, Jun Han
77
Voted
ICML
2006
IEEE
16 years 1 months ago
Topic modeling: beyond bag-of-words
Some models of textual corpora employ text generation methods involving n-gram statistics, while others use latent topic variables inferred using the "bag-of-words" assu...
Hanna M. Wallach
118
Voted
ISBI
2009
IEEE
15 years 7 months ago
Instance-Based Generative Biological Shape Modeling
Biological shape modeling is an essential task that is required for systems biology efforts to simulate complex cell behaviors. Statistical learning methods have been used to buil...
Tao Peng, Wei Wang, Gustavo K. Rohde, Robert F. Mu...