<div dir="ltr"><p style="box-sizing:border-box;margin:0px 0px 1.5rem;padding:0px;vertical-align:baseline;font-family:NexusSerif,Georgia,serif;font-size:18.8px;line-height:1.625rem;max-width:inherit;color:rgb(80,80,80)"><span style="box-sizing:border-box;margin:0px;padding:0px;vertical-align:baseline;line-height:inherit;font-weight:700"><u style="box-sizing:border-box;margin:0px;padding:0px;vertical-align:baseline"></u></span></p><h1 style="box-sizing:border-box;margin:0px 0px 0.373rem;padding:0px;vertical-align:baseline;font-family:NexusSerif,Georgia,serif;line-height:1.4;font-size:2.375rem;max-width:inherit;font-feature-settings:"kern","liga","pnum","tnum" 0,"onum","lnum" 0,"dlig";font-weight:100">Robust, Explainable, and Privacy-Preserving Deep Learning</h1><div><a href="https://www.journals.elsevier.com/knowledge-based-systems/call-for-papers/robust-explainable-and-privacy-preserving-deep-learning">https://www.journals.elsevier.com/knowledge-based-systems/call-for-papers/robust-explainable-and-privacy-preserving-deep-learning</a><br></div><div><br></div><p style="box-sizing:border-box;margin:0px 0px 1.5rem;padding:0px;vertical-align:baseline;font-family:NexusSerif,Georgia,serif;font-size:18.8px;line-height:1.625rem;max-width:inherit;color:rgb(80,80,80)"><span style="box-sizing:border-box;margin:0px;padding:0px;vertical-align:baseline;line-height:inherit;font-weight:700"><u style="box-sizing:border-box;margin:0px;padding:0px;vertical-align:baseline">Aim and Scope</u></span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">The exponentially growing availability of data such as
images, videos and speech from myriad sources, including social media and the
Internet of Things, is driving the demand for high-performance data analysis
algorithms. Deep learning is currently an extremely active research area in
machine learning and pattern recognition. It provides computational models of
multiple nonlinear processing neural network layers to learn and represent data
with increasing levels of abstraction. Deep neural networks are able to
implicitly capture intricate structures of large-scale data and deploy in cloud
computing and high-performance computing platforms. The deep learning approach
has demonstrated remarkable performances across a range of applications,
including computer vision, image classification, face/speech recognition,
natural language processing, and medical communications. However, deep neural
networks yield ‘black-box’ input-output mappings that can be challenging to
explain to users. Especially in the healthcare, cybersecurity, and legal
fields, black-box machine learning techniques are unacceptable, since decisions
may have a profound impact on peoples’ lives due to the lack of
interpretability. In addition, many other open problems and challenges still
exist, such as computational and time costs, repeatability of the results,
convergence, and the ability to learn from a very small amount of data and to
evolve dynamically. Further, despite their enormous societal benefits, deep
learning can pose real threats to personal privacy. For example, deep neural
networks and other machine learning models are built based on patients'
personal and highly sensitive data such as clinical records or tracked health
data in the domain of healthcare. Moreover, they can be vulnerable to attackers
trying to infer the sensitive data that was used to build the model. This
raises important research questions about how to develop deep learning models
that protect private data against inference attacks while still being accurate
and useful predictive models.</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">This Special Issue will present robust, explainable, and
efficient next-generation deep learning algorithms with data privacy and
theoretical guarantees for solving challenging artificial intelligence
problems. This Special Issue aims to: 1) improve the understanding and
explainability of deep neural networks; 2) improve the accuracy of deep
learning leveraging new stochastic optimization and neural architecture search;
3) enhance the mathematical foundation of deep neural networks; 4) design new
data privacy mechanisms to optimally tradeoff between utility and privacy; and
5) increase the computational efficiency and stability of the deep learning
training process with new algorithms that will scale. Potential topics include
but are not limited to the following:</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Novel theoretical insights on the
deep neural networks</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Exploration of post-hoc
interpretation methods which can shed light on how deep learning models produce
a specific prediction and generate a representation</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Investigation of interpretable
models which aim to construct self-explanatory models and incorporate
interpretability directly into the structure of a deep learning model</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Quantifying or visualizing the
interpretability of deep neural networks</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Stability improvement of deep
neural network optimization</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Optimization methods for deep
learning</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Privacy preserving machine
learning (e.g., federated machine learning, learning over encrypted data)</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Novel deep learning approaches in
the applications of image/signal processing, business intelligence, games,
healthcare, bioinformatics, and security</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Important Dates</span></b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)"></span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Submission Deadline: August 31,
2021</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">First Review Decision: September
30, 2021</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Revisions Due: October 31, 2021</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Final Decision: November 30, 2021</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Final Manuscript: December 31,
2021</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Dissemination, Composition and Review Procedures</span></b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)"></span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">A Call for Papers (CFP) will be
circulated to invite submissions.</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">World leading researchers will be
invited as authors.</span></p><p class="MsoNormal" align="left" style="margin:0cm 0cm 0.0001pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:10pt;font-family:Symbol;color:rgb(80,80,80)">·<span style="font-variant-numeric:normal;font-variant-east-asian:normal;font-stretch:normal;font-size:7pt;line-height:normal;font-family:"Times New Roman"">
</span></span><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">To further attracting
contributors from around the world, the CFP will be advertised across numerous
society newsletters, different websites, mailing lists, conferences,
associations, and social media groups, etc.</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)"><br></span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">This special issue will run as per the timeline given
from submission to publication, while maintaining the rigorous peer review and
high standards of the journal. All manuscripts submitted must be original, not
under consideration elsewhere, and not previously published. A guide for
authors and other relevant information for submission of manuscripts are
available on the Guide for Authors’ page. Authors can expect their manuscripts
to be reviewed fairly, and in a skilled, conscientious manner. To enhance
objectivity, and to guarantee high scientific quality and relevance to the
subject, three peer reviewers will be selected to evaluate a manuscript. The
peer review process shall be designed to avoid bias and conflict of interest on
the part of reviewers and shall be composed of experts in the relevant field of
research. A key criterion in publication decisions will be the manuscript’s fit
for the special issue and the readership of KBS. Papers will be published
online as soon as accepted in continuous flow.</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Submission Instructions</span></b><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)"></span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">The submission system will be open around one week before
the first paper comes in. When submitting your manuscript please select the
article type “<b>VSI: Deep Learning</b>”. Please submit your manuscript before
the submission deadline.</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">All submissions deemed suitable to be sent for peer
review will be reviewed by at least two independent reviewers. Once your
manuscript is accepted, it will go into production, and will be simultaneously
published in the current regular issue and pulled into the online Special
Issue. Articles from this Special Issue will appear in different regular issues
of the journal, though they will be clearly marked and branded as Special Issue
articles.</span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Please see an example here: <a href="https://www.sciencedirect.com/journal/science-of-the-total-environment/special-issue/10SWS2W7VVV"><span style="color:rgb(0,115,152);text-decoration-line:none">https://www.sciencedirect.com/journal/science-of-the-total-environment/special-issue/10SWS2W7VVV</span></a></span></p><p class="MsoNormal" align="left" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;vertical-align:baseline;margin:0cm 0cm 0.0001pt;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US" style="font-size:14pt;font-family:Georgia,serif;color:rgb(80,80,80)">Please ensure you read the Guide for Authors before
writing your manuscript. The Guide for Authors and the link to submit your
manuscript is available on the Journal’s homepage.</span></p><p style="box-sizing:border-box;margin:0px 0px 1.5rem;padding:0px;vertical-align:baseline;font-family:NexusSerif,Georgia,serif;font-size:18.8px;line-height:1.625rem;max-width:inherit;color:rgb(80,80,80)">
</p><p class="MsoNormal" style="margin:0cm 0cm 0.0001pt;text-align:justify;font-size:10.5pt;font-family:Calibri,sans-serif"><span lang="EN-US"> </span></p></div>