000			04542nam a22004815i 4500
999			_c387071 _d387071
001			387071
003			ES-MaUEC
005			20230211135826.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			230211s2021 sz | s |||| 0|eng d
020			_a9783031023804
024	7		_a10.1007/978-3-031-02380-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5105.8857 _b2021 EB
100	1		_aLin, Sen _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686737
245	1	0	_aEdge Intelligence in the Making ; _bOptimization, Deep Learning, and Applications _cby Sen Lin, Zhi Zhou, Zhaofeng Zhang, Xu Chen, Junshan Zhang
250			_a1st edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (CCXV, 17 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Learning Networks and Algorithms _x2690-4314
505	0		_aPreface -- Acknowledgments -- Introduction to Edge Intelligence -- Edge Intelligence via Model Training -- Edge-Cloud Collaborative Learning via Distributionally Robust Optimization -- Hierarchical Mobile-Edge-Cloud Model Training with Hybrid Parallelism -- Edge Intelligence via Model Inference -- On-Demand Accelerating Deep Neural Network Inference via Edge Computing -- Applications, Marketplaces, and Future Directions of Edge Intelligence -- Bibliography -- Authors' Biographies.
520			_aWith the explosive growth of mobile computing and Internet of Things (IoT) applications, as exemplified by AR/VR, smart city, and video/audio surveillance, billions of mobile and IoT devices are being connected to the Internet, generating zillions of bytes of data at the network edge. Driven by this trend, there is an urgent need to push the frontiers of artificial intelligence (AI) to the network edge to fully unleash the potential of IoT big data. Indeed, the marriage of edge computing and AI has resulted in innovative solutions, namely edge intelligence or edge AI. Nevertheless, research and practice on this emerging inter-disciplinary field is still in its infancy stage. To facilitate the dissemination of the recent advances in edge intelligence in both academia and industry, this book conducts a comprehensive and detailed survey of the recent research efforts and also showcases the authors' own research progress on edge intelligence. Specifically, the book first reviews the background and present motivation for AI running at the network edge. Next, it provides an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning models toward training/inference at the network edge. To illustrate the research problems for edge intelligence, the book also showcases four of the authors' own research projects on edge intelligence, ranging from rigorous theoretical analysis to studies based on realistic implementation. Finally, it discusses the applications, marketplace, and future research opportunities of edge intelligence. This emerging interdisciplinary field offers many open problems and yet also tremendous opportunities, and this book only touches the tip of iceberg. Hopefully, this book will elicit escalating attention, stimulate fruitful discussions, and open new directions on edge intelligence.
988			_aSynthesis Collection of Technology_2021
650		7	_2embne _9483083 _aInternet de los objetos
650		7	_2embne _9147646 _aSistemas de comunicación móviles
650		7	_2embne _9666069 _aInformática en la nube
700	1		_aZhou, Zhi-Hua _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9681254 _c(Computer scientist)
700	1		_aZhang, Zhaofeng _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686738
700			_aChen, Xu _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9668620
700	1		_aZhang, Junshan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686739
776	0	8	_iPrinted edition: _z9783031002441
776	0	8	_iPrinted edition: _z9783031012525
776	0	8	_iPrinted edition: _z9783031035081
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02380-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2023 _dz _eIG _zSI