<div dir="ltr"><div class="gmail_quote"><div dir="ltr" class="gmail_attr"><b>TL;DR – CFP:</b> Springer Book on GANs<br></div><div dir="ltr"><b>GUEST EDITORS</b>:
<span style="font-family:Roboto,RobotoDraft,Helvetica,Arial,sans-serif;font-size:14px">Roozbeh Razavi-Far,</span> <font size="2">Ariel Ruiz-Garcia, </font>Vasile Palade, <font size="2">Jürgen Schmidhuber</font><br><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b style="font-family:Arial,Helvetica,sans-serif;font-size:small">SUBMISSION DEADLINE</b><span style="font-family:Arial,Helvetica,sans-serif;font-size:small">: 15th April 2021</span><b><span style="font-size:12pt"> </span></b></p><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt"><br></span></b></p><p class="MsoNormal" align="center" style="margin:0in;text-align:center;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt">Call for Book Chapters</span></b><span style="font-size:12pt"></span></p><p class="MsoNormal" align="center" style="margin:0in;text-align:center;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" align="center" style="margin:0in;text-align:center;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:16pt;color:rgb(68,84,106)">Springer
book on: </span></b></p><p class="MsoNormal" align="center" style="margin:0in;text-align:center;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><i><span style="font-size:16pt;color:rgb(68,84,106)">Generative
Adversarial Learning: Architectures and Applications</span></i></b><span style="font-size:16pt;color:rgb(68,84,106)"></span></p><p class="MsoNormal" align="center" style="margin:0in;text-align:center;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Adversarial learning has fascinated the attention of artificial
intelligence and machine learning communities across the world over the last
years. Their success is achieved by exploiting a minimax learning concept,
which has proved to be an effective paradigm in earlier works, such as
adversarial curiosity (1990) and predictability minimization (1991), in which
two networks compete in a minimax game during the learning process. One of
their key advantages over other learning methods is the capability of generating
new data from random noise, as well as their capability to replicate data
distributions. However, producing real data using Generative Adversarial
Networks (GANs) remains a challenge, especially when particular features are
required; for instance, constraining the latent aggregate distribution space
does not guarantee that the generator will produce an image with a specific
attribute.</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Aside from realistic image generation, GANs have been
extensively used for numerous other application domains such as: speech and
audio synthesis, object detection and segmentation, policy learning in deep
reinforcement learning, etc., usually providing promising results. Despite
their apparent advantages and their application to a wide range of domains,
GANs have yet to overcome several challenges including model convergence, mode
collapse, vanishing gradients, model interpretability, and model sensitivity to
parameters and hyper-parameter initialization. Such problems often arise due to
the added complexity of simultaneous training of the generator and
discriminator models. Recent advancements in machine learning are expected to
provide efficient solutions to deal with the above raised challenges.</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">This book will provide a collection of high-quality research
articles addressing theoretical work for improving the learning process and the
generalization of GANs. State-of-the-art applications of GANs are also very
welcomed. This Springer edited book solicits contributed chapters including but
not limited to the following topics:</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt;color:black"> </span><span style="font-size:12pt"></span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Generative adversarial learning methods and theory;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial deep learning for domain adaptation;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Network interpretability in adversarial learning;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial feature learning; </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial learning for data augmentation;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial deep learning for class imbalance;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial deep learning for semi-supervised learning;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• New GAN models and new GAN learning criteria;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial deep learning in pattern recognition;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for noise reduction;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for imitation learning;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for image segmentation and image completion;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs in deep reinforcement learning;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for image and video synthesis;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for speech and audio synthesis;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• GANs for in-painting and sketch to image; </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Adversarial learning in Neural Machine Translation;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Object Compositionality in GANS;</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">• Applications of GANs in various domains, such as computer
vision, cyber security, safety, engineering, video inference, speech and
emotion recognition, voice conversion, natural language processing.</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt">Important Dates</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt"> </span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> 15<sup>th</sup> March
2021 – Abstract submission deadline</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> 15<sup>th</sup> April
2021 – Chapter submission deadline</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> 30<sup>th</sup> May
2021 – Chapter acceptance notification </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> 31<sup>st</sup> July
2021 – Camera-ready submission deadline</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> September 2021 – Book
publication</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt">Book Editors:</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt"> </span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt;color:rgb(68,84,106)">Dr Roozbeh Razavi-Far</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">University of Windsor, Canada</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span lang="ES-MX" style="font-size:12pt">Email: <a href="mailto:roozbeh@uwindsor.ca" target="_blank">roozbeh@uwindsor.ca</a></span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span lang="ES-MX" style="font-size:12pt"> </span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span lang="ES-MX" style="font-size:12pt;color:rgb(68,84,106)">Dr Ariel Ruiz-Garcia</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">SeeChange.ai, UK </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Email: <a href="mailto:ariel.9arcia@gmail.com" target="_blank">ariel.9arcia@gmail.com</a></span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt;color:rgb(68,84,106)">Professor Vasile Palade</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Coventry University, UK</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Email: <a href="mailto:vasile.palade@coventry.ac.uk" target="_blank">vasile.palade@coventry.ac.uk</a></span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span style="font-size:12pt;color:rgb(68,84,106)">Professor Jürgen Schmidhuber</span></b></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">NNAISENSE,</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Swiss AI Lab IDSIA,</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">USI & SUPSI, Switzerland</span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt">Email: <a href="mailto:juergen@idsia.ch" target="_blank">juergen@idsia.ch</a></span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span style="font-size:12pt"> </span></p><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><b><span lang="EN-GB" style="font-size:12pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Submission
Procedure:</span></b></p><p class="MsoNormal" style="margin:0in;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-GB" style="font-size:12pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"> </span></p><p class="MsoNormal" style="margin:0in;text-align:justify;line-height:normal;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial;font-size:11pt;font-family:Calibri,sans-serif"><span lang="EN-GB" style="font-size:12pt;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial">Prospective authors should</span><span style="font-size:12pt"> submit a tentative
title, names and affiliation of authors and a brief abstract with keywords of their
proposed contribution via </span><span style="color:black"><a href="https://easychair.org/conferences/?conf=genadvlearn-book-21" style="color:blue" target="_blank"><span style="font-size:12pt">EasyChair</span></a></span><span style="font-size:12pt">. Please also let the
editors know. We strongly encourage authors to submit abstracts as soon as
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