Special Session on Reservoir Computing: algorithms, implementations, and applications

IEEE World Congress on Computational Intelligence (WCCI 2022)
International Joint Conference on Neural Networks (IJCNN 2022)
18 - 23rd July 2022, Padoua (Italy)


Papers submission deadline: 31 January 2022
More info at: https://sites.google.com/view/reservoir-computing-tf/activities/wcci-2022-special-session
Submission link: https://cmt3.research.microsoft.com/IEEEWCCI2022/
Organizers
Claudio Gallicchio (University of Pisa, Italy), Fatemeh Hadaeghi (Universitätsklinikum Hamburg-Eppendorf (UKE), Germany), Miguel Cornelles Soriano (University of the Balearic Islands, Spain)

Description
Reservoir Computing (RC) approach for designing and training Recurrent Neural Networks (RNNs) has attracted a lot of attention in various fields of research due to its straightforward and efficient training process. Besides, RC neural networks are distinctively amenable to hardware implementations (including in neuromorphic unconventional substrates, like photonics), enable clean mathematical analysis (rooted, e.g., in the field of random matrix theory), and find natural applications in resource-constrained contexts, such as edge AI systems. Moreover, in the broader picture of Deep Learning development, RC is a breeding ground for testing innovative ideas, e.g. biologically plausible training algorithms beyond gradient back-propagation. Noticeably, although established in the Machine Learning field, RC lends itself naturally to interdisciplinarity, where ideas coming from diverse areas such as computational neuroscience, complex systems, and non-linear physics can lead to further developments and new applications.

This session intends to strongly encourage RC research within the international neural networks community, bringing ideas from other connected interdisciplinary fields. We then invite the researchers to submit papers on all aspects of RC research, targeting contributions on new algorithms, implementations, and applications.

Topics of Interests
A list of relevant topics for this session includes, without being limited to, the following:
§ New Reservoir Computing models and architectures, including Echo State Networks and Liquid State Machines
§ Hardware, physical and neuromorphic implementations, including spintronics, photonics, and quantum Reservoir Computing
§ Reservoir Computing in Computational Neuroscience
§ Reservoir Computing on the edge systems
§ Novel learning algorithms rooted in Reservoir Computing concepts
§ Novel applications of Reservoir Computing, e.g., to images, video, and structured data
§ Federated and Continual Learning in Reservoir Computing
§ Deep Reservoir Computing Neural Networks
§ Theory of complex and dynamical systems in Reservoir Computing
§ Extensions of the Reservoir Computing framework, such as Conceptors
§ Reservoir dimensionality reduction
§ Efficient reservoir hyper-parameter search

Important Dates
- Title and Abstract submission: January 31, 2022 (11:59 PM AoE). New submissions cannot be created past this deadline.
- Complete Paper (pdf) submission: February 14, 2022 (11:59 PM AoE) STRICT DEADLINE
- Decision notification: April 26, 2022
- Camera-ready paper: May 23, 2022

Submission Guidelines and Instructions
Papers submission for this Special Session follows the same process as for the regular sessions of WCCI 2022 (see https://wcci2022.org/submission/), which uses Microsoft CMT.
Submit your paper at the following link: https://cmt3.research.microsoft.com/IEEEWCCI2022/:
1) In the Author Console, click on Create Submission
2) In the drop-down menu, choose "IJCNN"
3) In the Subject Areas section, please indicate "IJCNN-SS-12 Reservoir Computing: algorithms, implementations, and applications" as the primary area.
* Important note: differently from previous editions, the review process for WCCI/IJCNN 2022 will be double-blind. For prospected authors, it is therefore mandatory to anonymize their manuscripts.
Paper Publication
Accepted papers will be published in the IJCNN conference proceedings (to be published by IEEE).


Sincerely,
Organizing Team