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, mostly tailored to the case of dynamic sequential inference and probabilistic recommender systems. The position is connected to the project “Bayesian Rank-based unsupervised Integration of multi-source
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Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference
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Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case of dynamic sequential inference and probabilistic
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