"Applications of Matrix Computational Methods in the Analysis of Modern Data"
June 12-14, 2017, Zürich, Switzerland
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE
Track - Workshop in
Applications of Matrix Computational Methods in the Analysis of "Modern Data"
Objectives and Description of the Workshop:
“Modern Data” has unique characteristics such as, extreme sparsity, high correlation, high dimensionality and massive size. Modern data
is very prevalent in all different areas of science such as Medicine, Environment, Finance, Marketing, Vision, Imaging, Text, Web, etc. A
major difficulty is that many of the old methods that have been developed for analyzing data during the last decades cannot be applied on
modern data. One distinct solution, to overcome this difficulty, is the application of matrix computation and factorization methods such as
SVD (singular value decomposition), PCA (principal component analysis), and NMF (non- negative matrix factorization), without which the
analysis of modern data is not possible. This workshop covers the application of matrix computational science techniques in dealing with
Modern Data.
Themes (not limited to)
Theoretical Aspects of “Modern Data”
Sparse Matrix Factorization
Recommender System
Dimension Reduction and Feature Learning
Deep Learning
Computational Cognition
Computational Finance
Image and Voice Recognition
Machine Learning Software Engineering
Singular Value Decomposition in “Modern Data”
Social Computing
Vision
NLP and Text Analytics
Biostatistics and Computational Biology
Graph Algorithms
Contact
Track Chair and Organizer: Kourosh Modarresi, kouroshm@alumni.stanford.edu
Program Committee
Ram Akella (UC Santa Cruz)
David Cavander (Adobe Inc.)
Walter Gander (ETH)
Christophe Giraud-Carrier (BYU)
Trevor Hastie (Stanford University)
Paul Hofmann (space-Time Insight)
Pradeep Javangula (Adobe Inc.)
Jeremy Kepner (MIT LL)
Roy Lettieri (CPG IND)
Lexin Li (UC Berkeley)
Akash Vivek Maharaj (Stanford)
Rahul Mazumder (MIT)
Kourosh Modarresi (Adobe Inc.)
James O'Keeffe (LiveSpace)
Raja P Velu (Syracuse University) -- Meeting Session Chair
Hongyuan Yuan (Adobe Inc)
Qi Zeng (Stanford)
Ji Zhu (University of Michigan)
Submit your paper via Easychair
Submission deadline is February 10th, 2017 . Please submit a short abstract now to indicate your interest.
Authors are invited to submit manuscripts reporting original, unpublished research and recent developments in Computational Sciences.
All accepted full papers will be included in the open-access Procedia Computer Science series and indexed by Scopus, ScienceDirect, Thomson Reuters
Conference Proceedings Citation (former ISI Proceedings) – an integrated index within Web of Science. The papers will contain linked references, XML
versions and citable DOI numbers.
Please submit your paper via the conference website at Easychair . Do Not Forget to select the "Applications of Matrix Computational
Methods in the Analysis of Modern Data" track when submitting.