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IDEAL
2004
Springer
15 years 4 months ago
Policy Gradient Method for Team Markov Games
The main aim of this paper is to extend the single-agent policy gradient method for multiagent domains where all agents share the same utility function. We formulate these team pro...
Ville Könönen
ICONIP
2009
14 years 9 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa
ICPR
2002
IEEE
16 years 10 days ago
Fractional Component Analysis (FCA) for Mixed Signals
This paper proposes the fractional component analysis (FCA), whose goal is to decompose the observed signal into component signals and recover their fractions. The uniqueness of o...
Asanobu Kitamoto
CSDA
2010
100views more  CSDA 2010»
14 years 9 months ago
Least squares estimation of nonlinear spatial trends
The goal of this work is to study the asymptotic and finite sample properties of an estimator of a nonlinear regression function when errors are spatially correlated, and when the...
Rosa M. Crujeiras, Ingrid Van Keilegom
FOCI
2007
IEEE
15 years 5 months ago
Opposite Transfer Functions and Backpropagation Through Time
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Mario Ventresca, Hamid R. Tizhoosh