CFP: Deep Learning and Tensor/Matrix
Decomposition for Applications in Neuroscience
--------------------------------------------------------------------------------------------------------------------------------
CALL
FOR PAPERS
DLAN 2018
Workshop
on Deep Learning and Tensor/Matrix Decomposition for Applications in
Neuroscience will be held in conjunction with ICDM 2018
November 17th, 2018,
Singapore
https://crei.skoltech.ru/cdise/icdm-2018-workshop/
---------------------------------------------------------------------------------------------------------------------------------
DLAN is a full day workshop, organized in conjunction with ICDM 2018.
The IEEE International Conference on Data Mining series (ICDM) has
established itself as the world’s premier research conference in data
mining. The main goal of current workshop is to bring together academics,
researchers and practitioners to discuss and reflect on recent challenges
in neuroscience in the context of Deep Learning.
The workshop is oriented to all potential applications of deep learning and
matrix/tensor decomposition and networks in feature extraction,
classification, recognition, segmentation, enhancing, clustering, anomaly
detection, and prediction of brain and behavior data – as applied to the
multi-modal brain data (MRI/fMRI/CT, EEG/MEG, and biomarker assays),
especially for mental disorders. Special focus will be made on the
practical aspects of how to design and train deep neural networks with
appropriate reduction of the dimensionality, to achieve high classification
performance and reliability.
Because of recent breakthroughs in machine learning, especially deep neural
networks, it is expected that physicians will be able to completely rely on
the machine interpretation of MRIs, CT, PET scans using deep learning in
the nearest future. Though deep neural networks have revolutionized
computer vision through the end-to-end learning (i.e., learning from the
raw data), it is still difficult to accomplish the early detection of the
major neurodegenerative diseases (such as ADHD, Autism, or Alzheimer’s)
with the neural networks today, partially due to the need for development
of optimization techniques in order to work with the Big Data in the most
efficient way. These and related topics will be addressed at this workshop.
IMPORTANT DATES
---------------------------
All deadlines are at 11:59PM Pacific Time.
WORKSHOP PAPER SUBMISSIONS August 7, 2018
WORKSHOP PAPER NOTIFICATION September 4, 2018
WORKHSOP DATE November 17, 2018
TOPICS OF INTEREST
--------------------------------
We aim for a focus on the applications of Deep Learning to analysis of
neuroimaging data. Topics of interests for the workshop include, but are
not limited to:
Magnetic Resonance Imaging (MRI) / functional Magnetic Resonance Imaging
(fMRI)
Electroencephalography (EEG)
Magnetoencephalography (MEG)
Positron Emission Tomography (PET)
Near-infrared spectroscopy (NIRS)
Computed Tomography (CT)
Behavioral Data
Physiological Data
Electromyography (EMG)
We encourage submissions describing innovative work in related fields that
address the issue of interpretability in applications of DL to
neuroscience.
SUBMISSION GUIDELINES
-------------------------------------
Paper submissions should be limited to a maximum of ten (10) pages, in the
IEEE 2-column format (link), including the bibliography and any possible
appendices. Submissions longer than 10 pages will be rejected without
review. Though the limit is 10 pages, papers with more than 8 pages will
need to pay extra page fee.
All submissions will be triple-blind reviewed by the Program Committee on
the basis of technical quality, relevance to scope of the conference,
originality, significance, and clarity. For further information, please
visit the ICDM guidelines page http://icdm2018.org/calls/call-for-papers/.
Manuscripts must be submitted electronically. We do not accept email
submissions. Online submission system is available here.
All the workshop dates might strictly follow the same deadlines as
described on ICDM website http://icdm2018.org/key-dates/:
Workshop paper submissions: August 7, 2018
Workshop paper notification: September 4, 2018
Camera-ready deadline and copyright forms: September 15, 2018
All the submissions should follow the same format and page limit as ICDM
regular submission: http://icdm2018.org/calls/call-for-papers/
All accepted papers will be included in the IEEE ICDM 2018 Workshops
Proceedings volume published by IEEE Computer Society Press, and will also
be included in the IEEE Xplore Digital Library. Therefore, papers must
not have been accepted for publication elsewhere or be under review for
another workshop, conferences or journals.
If you are considering submitting to the workshop and have questions
regarding the workshop scope or need further information, please do not
hesitate to contact the organizers at NeuroDLTensor (at) gmail.com.
ORGANIZERS
---------------------------
Andrzej Cichocki (Skoltech)
Alexander Bernstein (Skoltech)
Evgeny Burnaev (Skoltech)
Dmitry Dylov (Skoltech)
Ivan Oseledets (Skoltech)
CONTACT us at:
NeuroDLTensor (at) gmail.com
2018-06-12 20:06 GMT+03:00 Evgeny Burnaev <[log in to unmask]>:
> CALL FOR PAPERS
>
>
> DLAN 2018
>
> Workshop
> on Deep Learning and Tensor/Matrix Decomposition for Applications in
> Neuroscience will be held in conjunction with ICDM 2018
>
> November 17th, 2018,
> Singapore
>
>
>
> https://crei.skoltech.ru/
> cdise/icdm-2018-workshop/
>
>
>
> ------------------------------------------------------------
> ---------------------------------------------------------------------
>
> DLAN is a full day workshop, organized in conjunction with ICDM 2018.
>
>
>
> The IEEE International Conference on Data Mining series (ICDM) has
> established itself as the world’s premier research conference in data
> mining. The main goal of current workshop is to bring together academics,
> researchers and practitioners to discuss and reflect on recent challenges
> in neuroscience in the context of Deep Learning.
>
>
>
> The workshop is oriented to all potential applications of deep learning
> and matrix/tensor decomposition and networks in feature extraction,
> classification, recognition, segmentation, enhancing, clustering, anomaly
> detection, and prediction of brain and behavior data – as applied to the
> multi-modal brain data (MRI/fMRI/CT, EEG/MEG, and biomarker assays),
> especially for mental disorders. Special focus will be made on the
> practical aspects of how to design and train deep neural networks with
> appropriate reduction of the dimensionality, to achieve high classification
> performance and reliability.
>
>
>
> Because of recent breakthroughs in machine learning, especially deep
> neural networks, it is expected that physicians will be able to completely
> rely on the machine interpretation of MRIs, CT, PET scans using deep
> learning in the nearest future. Though deep neural networks have
> revolutionized computer vision through the end-to-end learning (i.e.,
> learning from the raw data), it is still difficult to accomplish the early
> detection of the major neurodegenerative diseases (such as ADHD, Autism, or
> Alzheimer’s) with the neural networks today, partially due to the need for
> development of optimization techniques in order to work with the Big Data
> in the most efficient way. These and related topics will be addressed at
> this workshop.
>
>
>
>
>
> IMPORTANT DATES
>
> ---------------------------
>
> All deadlines are at 11:59PM Pacific Time.
>
>
>
> WORKSHOP PAPER SUBMISSIONS August 7, 2018
>
> WORKSHOP PAPER NOTIFICATION September 4, 2018
>
> WORKHSOP DATE November 17, 2018
>
>
>
>
>
>
>
>
>
> TOPICS OF INTEREST
>
> --------------------------------
>
> We aim for a focus on the applications of Deep Learning to analysis of
> neuroimaging data. Topics of interests for the workshop include, but are
> not limited to:
>
>
>
> Magnetic Resonance Imaging (MRI) / functional Magnetic Resonance Imaging
> (fMRI)
>
> Electroencephalography (EEG)
>
> Magnetoencephalography (MEG)
>
> Positron Emission Tomography (PET)
>
> Near-infrared spectroscopy (NIRS)
>
> Computed Tomography (CT)
>
> Behavioral Data
>
> Physiological Data
>
> Electromyography (EMG)
>
>
>
> We encourage submissions describing innovative work in related fields that
> address the issue of interpretability in applications of DL to
> neuroscience.
>
>
>
>
>
> SUBMISSION GUIDELINES
>
> -------------------------------------
>
> We invite submission of unpublished original research papers that are not
> under review elsewhere. All papers will be peer reviewed. If accepted, at
> least one of the authors must attend the workshop to present their work.
> Paper submissions should be limited to a maximum of ten (10) pages, in the
> IEEE 2-column format (link), including the bibliography and any possible
> appendices. Submissions longer than 10 pages will be rejected without
> review. All submissions will be triple-blind reviewed by the Program
> Committee on the basis of technical quality, relevance to scope of the
> conference, originality, significance, and clarity. For further
> information, please visit the ICDM guidelines page
> http://icdm2018.org/calls/call-for-papers/.
>
>
>
> Manuscripts must be submitted electronically via the submission site.
>
> https://wi-lab.com/cyberchair/2018/icdm18/scripts/submit.
> php?subarea=S26&undisplay_detail=1&wh=/cyberchair/2018/
> icdm18/scripts/ws_submit.php
>
>
>
> We do not accept email submissions.
>
>
>
> Accepted papers will be published in the conference proceedings by the
> IEEE Computer SocietyPress.
>
>
>
> If you are considering submitting to the workshop and have questions
> regarding the workshop scope or need further information, please do not
> hesitate to contact the organizers at NeuroDLTensor (at) gmail.com.
>
>
>
>
>
>
>
>
>
>
>
> ORGANIZERS
>
> ---------------------------
>
> Andrzej Cichocki (Skoltech)
>
> Alexander Bernstein (Skoltech)
>
> Evgeny Burnaev (Skoltech)
>
> Dmitry Dylov (Skoltech)
>
> Ivan Oseledets (Skoltech)
>
>
>
>
>
> CONTACT us at:
>
> NeuroDLTensor (at) gmail.com
>
