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CIKM
2010
Springer
13 years 11 months ago
Discriminative factored prior models for personalized content-based recommendation
Most existing content-based filtering approaches including Rocchio, Language Models, SVM, Logistic Regression, Neural Networks, etc. learn user profiles independently without ca...
Lanbo Zhang, Yi Zhang 0001
BMCBI
2010
174views more  BMCBI 2010»
14 years 17 days ago
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based h
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...
Junbai Wang
BMCBI
2010
165views more  BMCBI 2010»
14 years 17 days ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
INFOCOM
2005
IEEE
14 years 6 months ago
Bayesian indoor positioning systems
— In this paper, we introduce a new approach to location estimation where, instead of locating a single client, we simultaneously locate a set of wireless clients. We present a B...
David Madigan, E. Einahrawy, R. P. Martin, Wen-Hua...
ICML
2004
IEEE
15 years 1 months ago
Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
Zhihua Zhang, Dit-Yan Yeung, James T. Kwok
ICML
2005
IEEE
15 years 1 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers