\sessionHeader{Wed2D: Nectar Track}{Sami Kaski}{Chem, LT4}
\timeTitlePeople{14:00--14:50}{Matrix Factorization as Search}{Kristian Kersting, Christian Bauckhage, Christian Thurau and Mirwaes Wahabzada} 

\abst{Simplex Volume Maximization (SiVM) exploits distance geometry for efficiently factorizing
gigantic matrices. It was proven successful in game, social media, and plant mining. 
Here, we review the distance geometry approach and argue that it generally  
suggests to factorize gigantic matrices using search-based instead of optimization techniques. }



\timeTitlePeople{14:50--15:40}{Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy}{Marco Lippi, Andrea Passerini, Marco Punta and Paolo Frasconi} 

\abst{We present an application of machine learning algorithms for the
  identification of metalloproteins and metal binding sites on a
  genome scale. An extensive evaluation conducted in combination with
  X-ray absorption spectroscopy shows the great potentiality of the
  approach.}

\sessionend

