KDD
2005
ACM
14 years 5 months ago
2005
ACM
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
GECCO
2005
Springer
14 years 5 months ago
2005
Springer
This paper proposes a novel technique for a program evolution based on probabilistic models. In the proposed method, two probabilistic distribution models with probabilistic depen...
GECCO
2005
Springer
14 years 5 months ago
2005
Springer
A powerful approach to search is to try to learn a distribution of good solutions (in particular of the dependencies between their variables) and use this distribution as a basis ...
ACISICIS
2005
IEEE
14 years 5 months ago
2005
IEEE
Uncertainty always exists as an unavoidable factor in any pervasive context-aware applications. This is mostly caused by the imperfectness and incompleteness of data. In this pape...
TARK
2007
Springer
14 years 5 months ago
2007
Springer
We investigate the discrete (finite) case of the Popper-Renyi theory of conditional probability, introducing discrete conditional probabilistic models for (multi-agent) knowledge...
ILP
2007
Springer
14 years 5 months ago
2007
Springer
Research over the past several decades in learning logical and probabilistic models has greatly increased the range of phenomena that machine learning can address. Recent work has ...
GECCO
2007
Springer
14 years 5 months ago
2007
Springer
There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them....
QEST
2007
IEEE
14 years 5 months ago
2007
IEEE
— Probabilistic models are widely used to analyze embedded, networked, and more recently biological systems. Existing numerical analysis techniques are limited to finitestate mo...
KI
2009
Springer
14 years 6 months ago
2009
Springer
This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system’s belief. Probabilistic models can be estimated by Maximum a po...
ICANN
2009
Springer
14 years 6 months ago
2009
Springer
Abstract. Modeling the statistical structure of natural images is interesting for reasons related to neuroscience as well as engineering. Currently, this modeling relies heavily on...