Kourosh Modarresi just sent me the following
Dear Igor,Here is the announcement:
Julie (Josse) recommended me to reach out about the meeting (Deadline for all submissions are 1/31/2015). I appreciate if you publicize the meeting through your network. Also, please do submit your own works for the meeting.
ICCS 2015, AMCMD Workshop: Applications of Matrix Computational Methods in the Analysis of “Modern Data”
I am the organizer of Applications of Matrix Computational Methods in the Analysis of “Modern Data” workshop at ICCS2015 (premier conference in Scientific Computing). This is the workshop site,
This is an exciting opportunity and I am looking forward to it to be a great meeting. There will be at least two great invited lectures, Stanford Professors Jure Leskovec and Trevor Hastie. The ICCS (International Conference On Computational Science) is to be held in Reykjavík, Iceland on 1-3 June, 2015.
The submission is open till 1/31/2015.
When using the ICCS2015 site (http://www.iccs-meeting.org/iccs2015/) directly, you will be directed to EasyChair for submissions. Please make sure that you choose “Applications of Matrix Computational Methods in the Analysis of Modern Data” track for your submission choice.
Some more info about the workshop:
ICCS 2015 – AMCMD Workshop
Applications of Matrix Computational Methods in the Analysis of “Modern Data”
Description: “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.
Sample Themes/Topics (not limited to the list):
- 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
- Biostatistics and Computational Biology
It is a great opportunity for researchers and practitioners in the related fields to present their works alongside works of some of the greatest scientists in this area.
Please feel free to pass this email to anyone may be interested and please let me know if you have any questions.
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