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» Selectivity Estimation using Probabilistic Models
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ICRA
2005
IEEE
145views Robotics» more  ICRA 2005»
15 years 10 months ago
Modeling the Static and the Dynamic Parts of the Environment to Improve Sensor-based Navigation
— This paper addresses the modeling of the static and dynamic parts of the scenario and how to use this information within a real sensor-based navigation system. The contribution...
Luis Montesano, Javier Minguez, Luis Montano
ACL
2004
15 years 6 months ago
Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins, Mark...
TIT
1998
123views more  TIT 1998»
15 years 4 months ago
The Minimum Description Length Principle in Coding and Modeling
—We review the principles of Minimum Description Length and Stochastic Complexity as used in data compression and statistical modeling. Stochastic complexity is formulated as the...
Andrew R. Barron, Jorma Rissanen, Bin Yu
ICMLA
2009
15 years 2 months ago
Improving Clinical Relevance in Ensemble Support Vector Machine Models of Radiation Pneumonitis Risk
Patients undergoing thoracic radiation therapy can develop radiation pneumonitis (RP), a potentially fatal inflammation of the lungs. Support vector machines (SVMs), a statistical...
Todd W. Schiller, Yixin Chen, Issam El-Naqa, Josep...
AROBOTS
2008
104views more  AROBOTS 2008»
15 years 4 months ago
Modeling dynamic scenarios for local sensor-based motion planning
This paper addresses the modeling of the static and dynamic parts of the scenario and how to use this information with a sensor-based motion planning system. The contribution in th...
Luis Montesano, Javier Minguez, Luis Montano