Using a distributed deep learning algorithm for analyzing big data in smart cities

[1]  Sergios Theodoridis,et al.  Adaptive Multiregression in Reproducing Kernel Hilbert Spaces: The Multiaccess MIMO Channel Case , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[2]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.

[3]  Antonio González Muñoz,et al.  A Set of Complexity Measures Designed for Applying Meta-Learning to Instance Selection , 2015, IEEE Transactions on Knowledge and Data Engineering.

[4]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[5]  Bhiksha Raj,et al.  Privacy-preserving speech processing: cryptographic and string-matching frameworks show promise , 2013, IEEE Signal Processing Magazine.

[6]  Guoyin Wang,et al.  A Rough Set-Based Method for Updating Decision Rules on Attribute Values’ Coarsening and Refining , 2014, IEEE Transactions on Knowledge and Data Engineering.

[7]  Martin Sarnovsky,et al.  Distributed boosting algorithm for classification of text documents , 2014, 2014 IEEE 12th International Symposium on Applied Machine Intelligence and Informatics (SAMI).

[8]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[9]  Cheng Wang,et al.  Using Stacked Generalization to Combine SVMs in Magnitude and Shape Feature Spaces for Classification of Hyperspectral Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Jason Weston,et al.  Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing , 2012, AISTATS.

[11]  Pascal Vincent,et al.  Representation Learning: A Review and New Perspectives , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[13]  Klaus-Robert Müller,et al.  Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment , 2013, IEEE Signal Processing Magazine.

[14]  Marimuthu Palaniswami,et al.  Internet of Things (IoT): A vision, architectural elements, and future directions , 2012, Future Gener. Comput. Syst..

[15]  Qihui Wu,et al.  Kernel-Based Learning for Statistical Signal Processing in Cognitive Radio Networks: Theoretical Foundations, Example Applications, and Future Directions , 2013, IEEE Signal Processing Magazine.

[16]  J. Razmi,et al.  Forecasting electricity consumption by clustering data in order to decline the periodic variable’s affects and simplification the pattern , 2009 .

[17]  Konstantinos Demertzis,et al.  FuSSFFra, a fuzzy semi-supervised forecasting framework: the case of the air pollution in Athens , 2018, Neural Computing and Applications.

[18]  Xue-wen Chen,et al.  Big Data Deep Learning: Challenges and Perspectives , 2014, IEEE Access.

[19]  Nicola Jones,et al.  Computer science: The learning machines , 2014, Nature.

[20]  TheodoridisSergios,et al.  Adaptive constrained learning in reproducing Kernel Hilbert spaces , 2009 .

[21]  U. Berardi,et al.  Smart Cities: Definitions, Dimensions, Performance, and Initiatives , 2015 .

[22]  Chu-Ren Huang,et al.  Multi-domain sentiment classification with classifier combination , 2011 .

[23]  Burr Settles,et al.  Active Learning Literature Survey , 2009 .

[24]  Melba M. Crawford,et al.  Active Learning: Any Value for Classification of Remotely Sensed Data? , 2013, Proceedings of the IEEE.

[25]  Qiang Yang,et al.  Bridging Domains Using World Wide Knowledge for Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[26]  Qihui Wu,et al.  A survey of machine learning for big data processing , 2016, EURASIP Journal on Advances in Signal Processing.

[27]  Bryan Scotney,et al.  Smart City Architecture and its Applications Based on IoT , 2015, ANT/SEIT.

[28]  Sergios Theodoridis,et al.  Adaptive Constrained Learning in Reproducing Kernel Hilbert Spaces: The Robust Beamforming Case , 2009, IEEE Transactions on Signal Processing.

[29]  Ronald C. Taylor.  An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics , 2010, BMC Bioinformatics.