國立虎尾科技大學 |

Recent Advances in Big Data and Deep Learning = Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Recent Advances in Big Data and Deep Learning/ edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita.
其他題名:	Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 /
其他作者:	Anguita, Davide.
面頁冊數:	X, 392 p. 142 illus., 89 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-16841-4
ISBN:	9783030168414

Recent Advances in Big Data and Deep Learning = Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 /
Recent Advances in Big Data and Deep LearningProceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 /[electronic resource] :edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita. - 1st ed. 2020. - X, 392 p. 142 illus., 89 illus. in color.online resource. - Proceedings of the International Neural Networks Society,12661-8141 ;. - Proceedings of the International Neural Networks Society,1.

On the trade-oﬀ between number of examples and precision of supervision in regression -- Distributed SmSVM Ensemble Learning -- Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach -- Fast transfer learning for image polarity detection -- Dropout for Recurrent Neural Networks -- Psychiatric disorders classification with 3D Convolutional Neural Networks -- Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions -- Deep-learning domain adaptation techniques for credit cards fraud detection -- Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks -- An information theoretic approach to the autoencoder -- Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning -- Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies.

This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference. .

ISBN: 9783030168414

Standard No.: 10.1007/978-3-030-16841-4doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: TA345-345.5

Dewey Class. No.: 620.00285

Recent Advances in Big Data and Deep Learning = Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 /
LDR:03539nam a22004095i 4500 001 1018023
003 DE-He213
005 20200702083903.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030168414 $9 978-3-030-16841-4
024 7 $a 10.1007/978-3-030-16841-4 $2 doi
035 $a 978-3-030-16841-4
050 4 $a TA345-345.5
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
072 7 $a TB $2 thema
082 0 4 $a 620.00285 $2 23
245 1 0 $a Recent Advances in Big Data and Deep Learning $h [electronic resource] : $b Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 / $c edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a X, 392 p. 142 illus., 89 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Proceedings of the International Neural Networks Society, $x 2661-8141 ; $v 1
505 0 $a On the trade-oﬀ between number of examples and precision of supervision in regression -- Distributed SmSVM Ensemble Learning -- Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach -- Fast transfer learning for image polarity detection -- Dropout for Recurrent Neural Networks -- Psychiatric disorders classification with 3D Convolutional Neural Networks -- Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions -- Deep-learning domain adaptation techniques for credit cards fraud detection -- Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks -- An information theoretic approach to the autoencoder -- Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning -- Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies.
520 $a This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference. .
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Computational Intelligence. $3 768837
650 1 4 $a Data Engineering. $3 1226308
650 0 $a Artificial intelligence. $3 559380
650 0 $a Computational intelligence. $3 568984
650 0 $a Engineering—Data processing. $3 1297966
700 1 $a Anguita, Davide. $e author. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1285108
700 1 $a Sperduti, Alessandro. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1312945
700 1 $a Navarin, Nicolò. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1312944
700 1 $a Oneto, Luca. $e author. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1285106
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030168407
776 0 8 $i Printed edition: $z 9783030168421
830 0 $a Proceedings of the International Neural Networks Society, $x 2661-8141 ; $v 1 $3 1312946
856 4 0 $u https://doi.org/10.1007/978-3-030-16841-4
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)