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» Improving the application of process models
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IROS
2009
IEEE
206views Robotics» more  IROS 2009»
15 years 10 months ago
Bayesian reinforcement learning in continuous POMDPs with gaussian processes
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
Patrick Dallaire, Camille Besse, Stéphane R...
WOSP
2000
ACM
15 years 8 months ago
Expressing meaningful processing requirements among heterogeneous nodes in an active network
Active Network technology envisions deployment of virtual execution environments within network elements, such as switches and routers. As a result, nonhomogeneous processing can ...
Virginie Galtier, Kevin L. Mills, Yannick Carlinet...
WSC
2004
15 years 5 months ago
Modeling and Simulation of Consumer Credit Originations Processes
Staffing decisions in a consumer credit origination environment have a significant impact on the financial institution's costs as well as customer service levels. Staff resou...
Hung-Nan Chen, Jihong Jin, Geetha Rajavelu, Charle...
PAMI
2008
182views more  PAMI 2008»
15 years 4 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
ICASSP
2010
IEEE
15 years 4 months ago
Multi-class SVM optimization using MCE training with application to topic identification
This paper presents a minimum classification error (MCE) training approach for improving the accuracy of multi-class support vector machine (SVM) classifiers. We have applied th...
Timothy J. Hazen