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NIPS
2000
13 years 10 months ago
High-temperature Expansions for Learning Models of Nonnegative Data
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Oliver B. Downs
JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
ICCSA
2009
Springer
14 years 3 months ago
Learning and Predicting Key Web Navigation Patterns Using Bayesian Models
Abstract. The accurate prediction of Web navigation patterns has immense commercial value as the Web evolves into a primary medium for marketing and sales for many businesses. Ofte...
Malik Tahir Hassan, Khurum Nazir Junejo, Asim Kari...
BPM
2009
Springer
175views Business» more  BPM 2009»
14 years 3 months ago
Understanding Spaghetti Models with Sequence Clustering for ProM
The goal of process mining is to discover process models from event logs. However, for processes that are not well structured and have a lot of diverse behavior, existing process m...
Gabriel M. Veiga, Diogo R. Ferreira
JMLR
2010
169views more  JMLR 2010»
13 years 3 months ago
Matrix-Variate Dirichlet Process Mixture Models
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
Zhihua Zhang, Guang Dai, Michael I. Jordan