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ALT
2004
Springer
14 years 6 months ago
Relative Loss Bounds and Polynomial-Time Predictions for the k-lms-net Algorithm
We consider a two-layer network algorithm. The first layer consists of an uncountable number of linear units. Each linear unit is an LMS algorithm whose inputs are first “kerne...
Mark Herbster
ICML
2009
IEEE
14 years 10 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
ICRA
2008
IEEE
197views Robotics» more  ICRA 2008»
14 years 4 months ago
A Bayesian framework for optimal motion planning with uncertainty
— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
ECSQARU
1995
Springer
14 years 1 months ago
Parametric Structure of Probabilities in Bayesian Networks
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Enrique Castillo, José Manuel Gutiér...
AAAI
1996
13 years 11 months ago
Goal Oriented Symbolic Propagation in Bayesian Networks
The paper presents an efficient goal oriented algorithm for symbolic propagation in Bayesian networks. The proposed algorithm performs symbolic propagation using numerical methods...
Enrique Castillo, José Manuel Gutiér...