Clustering - Main Issues
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ABSTRACT
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In this first lecture we discuss clustering 
as the prototypical unsupervised learning. 
We present the taxonomy of clustering: 
partitional and agglomerative, example of 
clustering algorithms, and the optimization 
approach to clustering. Ultrametric spaces, 
their geometry and applications to clustering 
are also presented.
          
SPEAKER(S)
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SIMOVICI Dan, Professor, PhD
Professor of Computer Science
University of Massachusetts, Department of Computer Science
Boston
S.U.A.
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Dr.Dan Simovici has been Professor of Computer Science at University
of Massachusetts Boston USA since 1985.His research focuses on
information-theoretical methods in data mining, semantic models
in databases and algebraic aspects of multiple-valued logic.Dr.Simovici
held several research and teaching positions at University of
Science and Technology, Lille, France, Tohoku University, Sendai,
Japan, and University of Miami, Florida.He is also an editor
of several scientific journals (e.g., Journal for Multiple-Valued
Logic and Soft Computing, International Journal for Parallel,
Emergent, and Distributed Systems, International Journal for
Software and Information Technologies, etc.).Dr.Simovici completed
his PhD in 1974 at the University of Bucharest, Romania, his
M.S. in Mathematics in 1970 at the Al. I. Cuza University of
Iasi, Romania and his M.S. in E.E. in 1965 at the Polytechnical
Institute of Iasi, Romania.
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