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ICASSP
2011
IEEE
13 years 14 days ago
Joint blind source separation from second-order statistics: Necessary and sufficient identifiability conditions
This paper considers the problem of joint blind source separation (J-BSS), which appears in many practical problems such as blind deconvolution or functional magnetic resonance im...
Javier Vía, Matthew Anderson, Xi-Lin Li, T&...
ICML
2004
IEEE
14 years 9 months ago
The multiple multiplicative factor model for collaborative filtering
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
Benjamin M. Marlin, Richard S. Zemel
PKDD
2009
Springer
170views Data Mining» more  PKDD 2009»
14 years 3 months ago
Statistical Relational Learning with Formal Ontologies
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...
Achim Rettinger, Matthias Nickles, Volker Tresp
NIPS
2008
13 years 10 months ago
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Indraneel Mukherjee, David M. Blei
FAST
2010
13 years 11 months ago
Understanding Latent Sector Errors and How to Protect Against Them
Latent sector errors (LSEs) refer to the situation where particular sectors on a drive become inaccessible. LSEs are a critical factor in data reliability, since a single LSE can ...
Bianca Schroeder, Sotirios Damouras, Phillipa Gill