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Annalisa Barla

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Position: Faculty Annalisa Barla
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Phone or fax: 6609
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My research mainly focuses on statistical learning techniques set in the context of regularization methods and applied to computational biology.


The analysis of biological data is characterized by a large amount of features representing each given example (high-dimensionality) and a relatively small number of samples. Traditional statistical tools were developed and studied to adapt in the opposite scenario, where the samples outnumber many times the variables, so different approaches have to be explored.

My main interests, from the algorithmic viewpoint are:

  • Supervised learning/classification methods
  • Kernel Engineering
  • Feature Selection
  • Vector valued regression/classification
  • Clustering techniques

From the methodological viewpoint, I am interested in studying statistical analysis algorithms which guarantee robustness and unbiased results, such as regularization techniques combined with validation methods to properly select the parameters:

  • significance assessment - complete validation
  • model selection

My other webpage is here and also here.

 

 

 
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