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Randomized Neural Networks - ESANN 2018 : Randomized Neural Networks - Special Session @ ESANN 2018

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Link: https://www.elen.ucl.ac.be/esann/index.php?pg=specsess#randomizedNN
 
When Apr 25, 2018 - Apr 27, 2018
Where Bruges, Belgium
Submission Deadline Nov 20, 2017
Notification Due Jan 31, 2018
Categories    neural networks   reservoir computing   echo state networks   machine learning
 

Call For Papers

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Scope and Topics
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The use of randomization in the design of Neural Networks (NNs) has become increasingly popular, mainly due to the ease of implementation, extreme efficiency of the training algorithms and the possibility of analyzing the NNs properties that are independent from learning. Randomization can enter NN design in various disguises, for example in the model construction and training (e.g. random setting of a subset of weights), or in its functionality and regularization algorithms (e.g. inclusion of random noise in activation layers, drop-out techniques, etc.). Under a broader perspective, the analysis of randomized models naturally extends to a general Machine Learning (ML) context (e.g. random projections). Moreover, Learning in Structured Domains and Deep Learning represent ML research areas for which this type of analysis is highly beneficial.

This session calls for contributions targeting novel theoretical and/or empirical studies on randomization in NNs, and it is proposed as an opportunity for discussing the advantages and limitations/shortcomings of the approach under an open and critical perspective.

The topics of interest for the session include, but are not limited, to the following:

-Neural Networks with random weights
-Randomized Machine Learning algorithms
-Reservoir Computing and Echo State Networks
-Extreme Learning Machines and Random Vector Functional-Link Networks
-Random Projections and Neural Networks
-Randomized regularization techniques
-Bias of randomization in the design of Neural Networks
-Theoretical analysis: advantages and shortcomings (range of applicability, stability, -efficiency, etc.)
-Deep Randomized Neural Networks
-Randomized approaches for Learning in Structured Domains (sequences, trees, graphs)
-Efficient implementations of Randomized Neural Networks
-Applications and comparisons

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Important Dates
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* Paper submission deadline: 20 November 2017

* Notification of acceptance: 31 January 2018

* ESANN conference: Bruges, Belgium, 25-27 April 2018

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Paper Submission
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Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of ESANN 2018. Authors who submit papers to this session are invited to mention it on the author submission form. Submissions to regular and special sessions follow identical format, instructions, deadlines and procedures.

Please find more info at the ESANN 2018 website https://www.elen.ucl.ac.be/esann/


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Special Session Organizers
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Claudio Gallicchio (University of Pisa, Italy),
Alessio Micheli (University of Pisa, Italy)
Peter Tino (University of Birmingham, United Kingdom)

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