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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 7 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
HICSS
2007
IEEE
138views Biometrics» more  HICSS 2007»
14 years 1 months ago
A Probabilistic Graphical Approach to Computing Electricity Price Duration Curves under Price and Quantity Competition
Abstract— The electricity price duration curve (EPDC) represents the probability distribution function of the electricity price considered as a random variable. The price uncerta...
Pascal Michaillat, Shmuel S. Oren
ECCV
2010
Springer
13 years 6 months ago
Object Recognition with Hierarchical Stel Models
Abstract. We propose a new generative model, and a new image similarity kernel based on a linked hierarchy of probabilistic segmentations. The model is used to efficiently segment ...
Alessandro Perina, Nebojsa Jojic, Umberto Castella...
EMNLP
2008
13 years 8 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
BMCBI
2004
166views more  BMCBI 2004»
13 years 6 months ago
Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models
Background: Many current gene prediction methods use only one model to represent proteincoding regions in a genome, and so are less likely to predict the location of genes that ha...
Shaun Mahony, James O. McInerney, Terry J. Smith, ...