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» Embedding Heterogeneous Data Using Statistical Models
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NIPS
2000
15 years 2 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
2012
13 years 3 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
SIGMOD
2010
ACM
259views Database» more  SIGMOD 2010»
15 years 5 months ago
PODS: a new model and processing algorithms for uncertain data streams
Uncertain data streams, where data is incomplete, imprecise, and even misleading, have been observed in many environments. Feeding such data streams to existing stream systems pro...
Thanh T. L. Tran, Liping Peng, Boduo Li, Yanlei Di...
92
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BMCBI
2008
93views more  BMCBI 2008»
15 years 24 days ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
IPMI
2001
Springer
16 years 1 months ago
Spatio-temporal Covariance Model for Medical Images Sequences: Application to Functional MRI Data
Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in...
Frithjof Kruggel, Habib Benali, Mélanie P&e...