Sciweavers

ICASSP
2010
IEEE
13 years 11 months ago
Learning in Gaussian Markov random fields
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Thomas J. Riedl, Andrew C. Singer, Jun Won Choi
TSP
2008
113views more  TSP 2008»
14 years 9 days ago
Covariance Matrix Estimation With Heterogeneous Samples
We consider the problem of estimating the covariance matrix of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly ...
Olivier Besson, Stéphanie Bidon, Jean-Yves ...
DAGSTUHL
2007
14 years 1 months ago
Learning Probabilistic Relational Dynamics for Multiple Tasks
The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
SIGIR
2004
ACM
14 years 5 months ago
A nonparametric hierarchical bayesian framework for information filtering
Information filtering has made considerable progress in recent years.The predominant approaches are content-based methods and collaborative methods. Researchers have largely conc...
Kai Yu, Volker Tresp, Shipeng Yu
ECML
2007
Springer
14 years 6 months ago
Bayesian Inference for Sparse Generalized Linear Models
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...