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BMCBI
2010
216views more  BMCBI 2010»
14 years 5 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...
ICML
2006
IEEE
15 years 10 months ago
Bayesian learning of measurement and structural models
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
Ricardo Silva, Richard Scheines
BIBE
2008
IEEE
137views Bioinformatics» more  BIBE 2008»
15 years 4 months ago
A sparse variational Bayesian approach for fMRI data analysis
— The aim of this work is to propose a new approach for the determination of the design matrix in fMRI experiments. The design matrix embodies all available knowledge about exper...
Vangelis P. Oikonomou, Evanthia E. Tripoliti, Dimi...
ACMMSP
2006
ACM
260views Hardware» more  ACMMSP 2006»
15 years 4 months ago
Seven at one stroke: results from a cache-oblivious paradigm for scalable matrix algorithms
A blossoming paradigm for block-recursive matrix algorithms is presented that, at once, attains excellent performance measured by • time, • TLB misses, • L1 misses, • L2 m...
Michael D. Adams, David S. Wise
NIPS
2008
14 years 11 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong