Plenary Lecture
Clustering Digital Data by Compression: Applications to Biology and Remote Sensing
Associate Professor Bruno Carpentieri
Department of Computer Science
University of Salerno
ITALY
E-mail: bc@dia.unisa.it
Abstract: Data compression, data prediction, data classification, learning and data mining are all facets of the same (multidimensional) coin. Compression also inspires information theoretic tools for clustering, pattern discovery and classification.
For example it has been recently proposed a new, “blind”, approach to clustering by compression that classifies digital objects depending on how they pair-wise compress.
We will review this clustering method and we will show how this approach can be used in bio-sequences clustering and remote sensing applications.
Brief Biography of the Speaker: Bruno Carpentieri received the “Laurea” degree in Computer Science from the University of Salerno, Salerno, Italy, and the M.A. and Ph.D. degrees in Computer Science from the Brandeis University, Waltham, MA, U.S.A.
Since 1991, he has been first Assistant Professor and then Associate Professor of Computer Science at the University of Salerno (Italy).
His research interests include lossless and lossy image compression, video compression and motion estimation, information hiding.
He has been, from 2002 to 2008, Associate Editor of the journal IEEE Trans. on Image Processing.
He was recently chair and organizer of the International Conference on Data Compression, Communication and Processing 2011, co-chair of the International Conference on Compression and Complexity of Sequences, and, for many years, program committee member of the IEEE Data Compression Conferente and of other international Conferences in the field.
He has been responsible for various European Commission contracts regarding image and video compression.