Seminar on Computer Science and Applied Mathematics
PROGRAM
Upravni odbor Matematickog instituta SANU je na nedavnoj sednici doneo odluku da se dosadasnji Seminar za primenjenu matematiku, sada nazove Seminar za racunarstvo i primenjenu matematiku, a u cilju potenciranja znacaja racunarstva kao jedne od oblasti delatnosti Instituta. Istovremeno, Upravni odbor doneo je odluku o osnivanju Odeljenja za racunarstvo i primenjenu matematiku i vezao rad novog odeljenja za rad Seminara za racunarstvo i primenjenu matematiku.
Petak, 15.08.2014. u 14:15, Sala 301f, MI SANU:
Joint meeting with Mathematics Colloquium
Zoran Obradovic, L.H. Carnell Professor of Data Analytics Director, Data
Analytics and Biomedical Informatics Center, Professor, Computer and
Information Sciences Department, Professor, Statistics Department, Fox
School of Business (secondary appointment), Temple University
UTILIZING TEMPORAL PATTERNS FOR ESTIMATING UNCERTAINTY IN INTERPRETABLE
EARLY DECISION MAKING
Abstract: Providing classification of time series as early as possible is
vital in many domains including the medical, where early diagnosis can save
patients. lives by providing early treatment. However, applications often
require the method to be interpretable and have uncertainty estimates. These
two aspects were not jointly addressed in previous studies, such that a
difficult choice of selecting one of these aspects is required. To address
this problem, in this study we propose a simple and yet effective method to
provide uncertainty estimates for an interpretable early classification
algorithm recently developed in our laboratory. The question we address here
is "how to provide estimates of uncertainty in regard to interpretable early
prediction." We showed that the proposed method is more effective than the
state-of-the-art alternatives in providing reliability estimates in early
classification, is simple to implement, and provides interpretable results.
This is joint research with M. Ghalwash and V. Radosavljevic and the results
will be published at the Proc. 20th ACM SIGKDD Conf. on Knowledge Discovery
and Data Mining, New York, NY, Aug. 2014.
Biography: Zoran Obradovic is a L.H. Carnell Professor of Data Analytics at
Temple University, Professor in the Department of Computer and Information
Sciences with a secondary appointment in Statistics, and is the Director of
the Center for Data Analytics and Biomedical Informatics. His research
interests include data mining and complex networks applications in health
management. Zoran is the executive editor at the journal on Statistical
Analysis and Data Mining, which is the official publication of the American
Statistical Association and is an editorial board member at eleven journals.
He was general co-chair for 2013 and 2014 SIAM International Conference on
Data Mining and was the program or track chair at many data mining and
biomedical informatics conferences. In 2014-2015 he chairs the SIAM Activity
Group on Data Mining and Analytics. His work is published in about 300
articles and is cited more than 13,000 times (H-index 44). For more details
see http://www.dabi.temple.edu/~zoran/
RUKOVODIOCI SEMINARA
MI SANU
Vera Kovačević-Vujčić
Milan Dražić
FON
Zorica Bogdanovic
Marijana Despotovic-Zrakic
IEEE
Bozidar Radenkovic