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DSP
2007
15 years 3 months ago
Variational and stochastic inference for Bayesian source separation
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...
Ali Taylan Cemgil, Cédric Févotte, S...
152
Voted
JMLR
2006
169views more  JMLR 2006»
15 years 3 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
ICSNC
2007
IEEE
15 years 9 months ago
Movement Prediction Using Bayesian Learning for Neural Networks
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
Sherif Akoush, Ahmed Sameh
RECOMB
2008
Springer
16 years 3 months ago
A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics
The protein inference problem represents a major challenge in shotgun proteomics. Here we describe a novel Bayesian approach to address this challenge that incorporates the predict...
Yong Fuga Li, Randy J. Arnold, Yixue Li, Predrag R...
129
Voted
ETFA
2006
IEEE
15 years 9 months ago
Advance in Multiply Sectioned Bayesian Networks: Sensor Network Practitioners' Perspective
Multiplysectioned Bayesian networks provide a probabilistic framework for reasoning about uncertain domains in cooperative multiagent systems. Several advances have been made in r...
Y. Xiang, K. Zhang