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AAAI
2006
13 years 11 months ago
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
Hoifung Poon, Pedro Domingos
EUSFLAT
2009
124views Fuzzy Logic» more  EUSFLAT 2009»
13 years 7 months ago
A toward Framework for Generic Uncertainty Management
The need for an automatic inference process able to deal with information coming from unreliable sources is becoming a relevant issue both on corporate networks and on the open Web...
Ernesto Damiani, Paolo Ceravolo, Marcello Leida
PR
2011
13 years 4 months ago
A variational Bayesian methodology for hidden Markov models utilizing Student's-t mixtures
The Student’s-t hidden Markov model (SHMM) has been recently proposed as a robust to outliers form of conventional continuous density hidden Markov models, trained by means of t...
Sotirios Chatzis, Dimitrios I. Kosmopoulos
AI
2007
Springer
14 years 3 months ago
Learning Network Topology from Simple Sensor Data
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...
Dimitri Marinakis, Philippe Giguère, Gregor...
BIBM
2007
IEEE
135views Bioinformatics» more  BIBM 2007»
14 years 4 months ago
Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network
Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li