ICCS 2015, AMCMD Workshop


 "Applications of Matrix Computational Methods in the Analysis of  Modern Data” Workshop

Reykjavik, Iceland   June 1-3, 2015


                  ICCS 2015


                         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.

Program Schedule (NEW)

 Applications of Matrix Computational Methods in the Analysis of Modern Data (MATRIX) Session 1

Time and Date: 10:15 - 11:55 on 3rd June 2015

Room: M209

Chair and Organizer: Kouroush Modarresi

Paul Hofmann
Daniel Serrano 

761 Matrix Completion via Fast Alternating Least Squares(40 Min) [abstract]  Trevor Hastie (Keynote Speaker)
93 Stable Autoencoding: A Flexible Framework for Regularized Low-Rank Matrix Estimation (20 min) [abstract] Julie Josse, Stefan Wager
349 Finding Top UI/UX Design Talent on Adobe Behance (20 min) [abstract] Susanne Halstead, Daniel Serrano, Scott Proctor
753 Graphs, Matrices, and the GraphBLAS: Seven Good Reasons (20 min) [abstract] Jeremy Kepner

Applications of Matrix Computational Methods in the Analysis of Modern Data (MATRIX) Session 2

Time and Date: 14:10 - 15:50 on 3rd June 2015

Room: M209

Chair: Kouroush Modarresi

762 Anomaly Detection and Predictive Maintenance through Large Sparse Similarity Matrices and Causal Modeling (35 min) [abstract] Paul Hofmann
692 Computation of Recommender System using Localized Regularization (20 min) [abstract] Kourosh Modarresi
695 Unsupervised Feature Extraction using Singular Value Decomposition (20 min) [abstract] Kourosh Modarresi
384 Quantifying complementarity among strategies for influencers' detection on Twitter (15 min) [abstract] Alan Neves, Ramon Viera, Fernando Mourão, Leonardo Rocha
399 Fast Kernel Matrix Computation for Big Data Clustering (15 min) [abstract] Nikolaos Tsapanos, Anastasios Tefas, Nikolaos Nikolaidis, Alexandros Iosifidis, Ioannis Pitas

Themes (not limited to)

Theoretical Aspects of “Modern Data”

Sparse Matrix Factorization

Recommender System

Dimension Reduction and Feature Learning

Deep Learning

Computational Finance

Singular Value Decomposition in “Modern Data”

Social Computing


NLP and  Text Analytics

Biostatistics and Computational Biology

Graph Algorithms


Track Chair and Organizer: Kourosh Modarresikouroshm@alumni.stanford.edu

Invited Lectures

Trevor Hastie (Stanford University, Stats)

Paul Hofmann (Space-Time Insight)

Program Committee

Ram Akella (UC Santa Cruz)

Trevor Hastie (Stanford University)

Paul Hofmann (Space-Time Insight)

Julie Josse (Agrocampus Ouest)

Jeremy Kepner (MIT LL)

Tse L Lai (Stanford University)

Roy Lettieri (CPG IND)

Lexin Li (UC Berkeley)   

Rahul Mazumder (Columbia University)

Kourosh Modarresi (Adobe Inc. and Stanford University)                              

Andre Neves (Imperial College)

James O'Keeffe (LiveSpace)

Hersir Sigurgeirsson (University of Iceland)

Bongwon Suh (Seol National university)

Raja P Velu (Syracuse University) 

Ji Zhu (University of Michigan)

Program Sessions (more sessions to be added later)

Graph Algorithms (Chair: Jeremy Kepner, MIT LL)

Call for Paper Submissions

"Authors are invited to submit manuscripts reporting original, unpublished research and recent developments in any of the workshop themes. All accepted 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.

The manuscripts of up to 10 pages, written in English and formatted according to the Easychair templates, should be submitted electronically. Papers must be based on unpublished original work and must be submitted to ICCS only. Submission implies the willingness of at least one of the authors to register and present the paper. Copyright forms are only needed after the paper has been accepted for publication in the proceedings.

Deadlines for draft paper submission, notification of acceptance, camera-ready paper submission and registration may be found in the Important Dates section.

After the conference, selected papers will be invited for a special issue of the Journal of Computational Science (Impact Factor 1.567)

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.

Important Dates

Full Paper Submission             January 15, 2015    January 31, 2015

Notification of Acceptance                    February 15, 2015   March 8, 2015

Camera-Ready Papers                         March 15, 2015       March 31, 2015

Author Registration                               March 8 – March 31, 2015