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February 2022

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Entropy Special Issue : Formal Analysis of Deep Artificial Neural Networks
by Friedhelm Schwenker Feb. 1, 2022

Feb. 1, 2022

Dear Researchers, The Entropy Journal (https://www.mdpi.com/journal/entropy) is currently running a Special Isuue on Formal Analysis of Deep Artificial Neural Networks <https://www.mdpi.com/journal/entropy/special_issues/DANN> (Deadline: *31 May 2022) *This Special Issue welcomes original research papers on the analysis of ANNs based on mathematically founded methods in general. Review articles describing the current state of the art of ANNs in the aforementioned contexts are highly encouraged. All submissions to this Special Issue must include substantial theoretical aspects of ANN research.* * Keywords * ANN architectures and learning in approximation and complexity theories * Cost functions and constraints in information-theoretic learning algorithms for ANNs * Complexity of deep, recurrent, or quantum ANN learning * Information-theoretic principles for sampling and feature extraction * Analysis of learning based on information-theoretic methods (e.g., information bottleneck approach) in deep, recurrent, or quantum ANNs * Applications of ANNs based on information-theoretic principles or quantum computing * Theoretical advances in quantum ANNs Please contact us: Edmondo Trentin <trentin(a)dii.unisi.it> or Friedhelm Schwenker <friedhelm.schwenker(a)uni-ulm.de> if you are interested in submitting your work. A number of waivers / discounts is available for interested authors. Best wishes, Friedhelm Schwenker Edmondo Trentin -- Prof. Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email:friedhelm.schwenker@uni-ulm.de www:http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html

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FLAIRS-35 May 15-18, 2022, Jensen Beach, Florida, Paper Deadline
by David B Feb. 1, 2022

Feb. 1, 2022

FLAIRS-35 Special Track on Neural Networks and Data Mining The Florida Artificial Intelligence Research Symposium (FLAIRS) is an interdisciplinary conference which features double-blind reviewing, free tutorials, and a warm and sunny venue. Abstract Due Date: February 7, 2022 Submission Due Date: February 14, 2022 Conference: May 15-18, 2022 Jensen Beach, Florida Website: https://sites.google.com/view/flairs-35-nn-dm-track/home URL: https://www.flairs-35.info/call-for-papers Papers are being solicited for a special track on Neural Networks and Data Mining at the 35th International FLAIRS Conference (https://www.flairs-35.info/home) This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy Logic applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction; and knowledge engineering or warehousing. Questions regarding the track should be addressed to: David Bisant at bisant(a)umbc.edu, Steven Gutstein at s.m.gutstein(a)gmail.com, or Bill Eberle at weberle(a)tntech.edu.

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