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» Structured Learning with Approximate Inference
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ICML
2009
IEEE
15 years 10 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
15 years 3 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
15 years 10 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor
ESWS
2005
Springer
15 years 3 months ago
Semantic-Based Automated Composition of Distributed Learning Objects for Personalized E-Learning
Recent advances in e-learning techonologies and web services make realistic the idea that courseware for personalized e-learning can be built by dynamic composition of distributed ...
Simona Colucci, Tommaso Di Noia, Eugenio Di Sciasc...
UAI
2000
14 years 11 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling