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IJCAI
2001
15 years 4 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
UAI
2001
15 years 4 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller
ICML
2004
IEEE
16 years 3 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh
ISBI
2006
IEEE
16 years 3 months ago
A novel approximate inference approach to automated classification of protein subcellular location patterns in multi-cell images
The subcellular location of proteins is most often determined by visual interpretation of fluorescence microscope images. In recent years, automated systems have been developed so...
Shann-Ching Chen, Geoffrey J. Gordon, Robert F. Mu...
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
16 years 3 months ago
Bypass rates: reducing query abandonment using negative inferences
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong