A Help for Those Who Make Predictions
DNA sequencing is an important tool in Genomics, Biotech and Medicine. Genomic libraries typically consist of millions of elements. Because of cost and/or time constraints, often only a sample is available, which corresponds to a small fraction of the library. Hence, in order to determine the number of new genes to be discovered in an additional sample or other quantities related to genetic diversity, statistical inference becomes essential.
However, the available predictive methodologies become unstable when prediction is required over a portion of the library larger than the one already sequenced. This limitation has been overcome by the results of Igor Pruenster's (Department of Decision Sciences) project New Directions in Bayesian Nonparametrics (N-BNP) hosted by IGIER - Innocenzo Gasparini Institute for Economic Research, funded with an ERC Starting Grant. Bayesian nonparametric inference is characterized by a high degree of flexibility, which allows to effectively model complex phenomena and to quantify their uncertainty. The applications considered in the project, in addition to Genomics, concern Ecology, Economics and even Privacy.
"Anonymizing collected personal data might not be enough to guarantee privacy of individuals or classes of individuals." One of the main themes consists in developing rigorous learning mechanisms and in describing their impact on predictions. "Given the extremely limited public funding in Italy", Pruenster notes, "the European Research Council represents an essential resource for basic research".
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Even Distorted Choices can be Rational
The Psychology of Economic Behavior
Great Expectations for Great Objectives
What we are Certain about Uncertainty
Putting a Halt to the Spread of Infections
Wellbeing and Fertility, a Two-Way Relationship
The Role of Financial Imperfections
The World Through the Lens of Power
The Selection of the Political Class
How to Evaluate Innovative Ideas
When a Government is Guided by Values