* Advances in Reservoir Computing*

Special Session for the 2018 IEEE World Congress on Computational Intelligence (WCCI) 2018
The International Joint Conference on Neural Networks (IJCNN) 2018
https://sites.google.com/view/reservoir-computing-ijcnn-2018

Paper submission deadline: *extended* 1 February 2018
IEEE WCCI conference: 8-13 July 2018, Rio de Janeiro, Brazil

* Scope and Topics *
During the last decade, Reservoir Computing (RC) has attested itself as a state of the art paradigm for efficient learning in the temporal domain. The extreme efficiency of the approach follows from limiting the training algorithm to only a readout component, while the temporal encoding process is carried out by a dynamical pool of recurrent neurons that, under certain conditions, is able to develop a rich representation of the temporal information even if untrained. The common paradigm has been instantiated into several models, among which the Echo State Network and the Liquid State Machine represent the most widely known ones.
Since its origins, we have witnessed a progressively increasing popularization of the RC approach, especially by virtue of its ease of implementation and its extreme training efficiency. At the same time, several theoretical research lines strongly contributed in understanding the bias of untrained recurrent models, grounding the RC methodology on a solid mathematical basis and better delineating the potentialities and downsides of the approach.
After 10 years since the introduction of the term "Reservoir Computing" into the neural networks literature, it is now time to sum up all the recent research initiatives in the field and start drawing its future. This session calls for both theoretical and applicative contributions emerging in the field of RC, aiming at stimulating an open discussion in the neural network community.

The list of relevant topics for this session includes, but is not limited to, the following:

Novel Reservoir Computing models
Theoretical analysis of Reservoir Computing
Physical implementations of Reservoir Computing
Evolutions of the RC paradigm (e.g., conceptors)
Biological motivations and applications in Neuroscience of Reservoir Computing
Adaptation of reservoir dynamics and of system dynamics
Deep Reservoir Computing models
Reservoir Computing for learning in structured domains (trees, graphs, networks, ...)
Reservoir Computing for Big Data
Novel application fields for the RC paradigm

* Important Dates *
Paper submission deadline: *extended* 1 February 2018
Notification of acceptance: 15 March 2018
IEEE WCCI conference: 8-13 July 2018, Rio de Janeiro, Brazil

* Papers Submission *
Papers submission for this Special Session follows the same process as for the regular sessions of WCCI 2018. For further information and news in this regard, please refer the WCCI 2018 website: http://www.ecomp.poli.br/~wcci2018/

* Special Session Organizers *

Claudio Gallicchio, (University of Pisa, Italy), Alessio Micheli, (University of Pisa, Italy), Simone Scardapane (Sapienza University, Italy), Peter Tiňo (University of Birmingham, UK).