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» Object-Oriented Bayesian Networks
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106
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TROB
2008
207views more  TROB 2008»
15 years 14 days ago
Learning Object Affordances: From Sensory-Motor Coordination to Imitation
Affordances encode relationships between actions, objects and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the p...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
95
Voted
CVIU
2004
94views more  CVIU 2004»
15 years 13 days ago
Video-based event recognition: activity representation and probabilistic recognition methods
We present a new representation and recognition method for human activities. An activity is considered to be composed of action threads, each thread being executed by a single act...
Somboon Hongeng, Ramakant Nevatia, François...
108
Voted
COLING
2002
15 years 12 days ago
Towards a Noise-Tolerant, Representation-Independent Mechanism for Argument Interpretation
We describe a mechanism for the interpretation of arguments, which can cope with noisy conditions in terms of wording, beliefs and argument structure. This is achieved through the...
Ingrid Zukerman, Sarah George
117
Voted
IJUFKS
2000
111views more  IJUFKS 2000»
15 years 12 days ago
A Factorized Representation of Independence of Causal Influence and Lazy Propagation
Theefficiency of algorithmsfor probabilistic inference in Bayesian networks can be improvedby exploiting independenceof causal influence. Thefactorized representation of independe...
Anders L. Madsen, Bruce D'Ambrosio
88
Voted
NECO
2002
104views more  NECO 2002»
15 years 7 days ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen