語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Advances in Data Science
~
Wang, Xu.
Advances in Data Science
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Advances in Data Science/ edited by Ilke Demir, Yifei Lou, Xu Wang, Kathrin Welker.
其他作者:
Welker, Kathrin.
面頁冊數:
XX, 364 p. 185 illus., 166 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Probability and Statistics in Computer Science. -
電子資源:
https://doi.org/10.1007/978-3-030-79891-8
ISBN:
9783030798918
Advances in Data Science
Advances in Data Science
[electronic resource] /edited by Ilke Demir, Yifei Lou, Xu Wang, Kathrin Welker. - 1st ed. 2021. - XX, 364 p. 185 illus., 166 illus. in color.online resource. - Association for Women in Mathematics Series,262364-5741 ;. - Association for Women in Mathematics Series,1.
Part I: Image Processing -- Two-stage Geometric Information Guided Image Processing (J. Qin and W. Guo) -- Image Edge Sharpening via Heaviside Substitution and Structure Recovery (L. Deng, W. Guo, and T. Huang) -- Two-step Blind Deconvolution of UPC-A Barcode Images (B. Kim and Y. Lou) -- Part II: Shape and Geometry -- An Anisotropic Local Method for Boundary Detection in Images (M. Lund, M. Howard, D. Wu, R. S. Crum, D. J. Miller, and M. C. Akin) -- Towards Learning Geometric Shape Parts (A. Fondevilla, G. Morin, and K. Leonard) -- Machine Learning in LiDAR 3D Point Clouds (F. P. Medina and R. Paffenroth) -- Part III: Machine Learning -- Fitting Small Piece-wise Linear Neural Network Models to Interpolate Data Sets (L. Ness) -- On Large-Scale Dynamic Topic Modelling with Nonnegative CP Tensor Decomposition (M. Ahn, N. Eikmeier, J. Haddock, L. Kassab, A. Kryshchenko, K. Leonard, D. Needell, R. W. M. A. Madushani, E. Sizikova, and C. Wang) -- A Simple Recovery Framework for Signals with Time-Varying Sparse Support (N. Durgin, R. Grotheer, C. Huang, S. Li, A. Ma, D. Needell, and J. Qin) -- Part IV: Data Analysis -- Role Detection and Prediction in Dynamic Political Networks (E. Evans, W. Guo, A. Genctav, S. Tari, C. Domeniconi, A. Murillo, J. Chuang, L. AlSumait, P. Mani, and N. Youssry) -- Classifying Sleep States Using Persistent Homology and Markov Chains: A Pilot Study (S. Tymochko, K. Singhal, and G. Heo) -- A Survey of Statistical Learning Techniques as Applied to Inexpensive Pediatric Obstructive Sleep Apnea Data (E. T. Winn, M. Vazquez, P. Loliencar, K. Taipale, X. Wang, and G. Heo) -- Nonparametric Estimation of Blood Alcohol Concentration from Transdermal Alcohol Measurements Using Alcohol Biosensor Devices (A. Kryshchenko, M. Sirlanci, and B. Vader).
This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources.
ISBN: 9783030798918
Standard No.: 10.1007/978-3-030-79891-8doiSubjects--Topical Terms:
669886
Probability and Statistics in Computer Science.
LC Class. No.: QA315-316
Dewey Class. No.: 515.64
Advances in Data Science
LDR
:04634nam a22004335i 4500
001
1057507
003
DE-He213
005
20211129224220.0
007
cr nn 008mamaa
008
220103s2021 sz | s |||| 0|eng d
020
$a
9783030798918
$9
978-3-030-79891-8
024
7
$a
10.1007/978-3-030-79891-8
$2
doi
035
$a
978-3-030-79891-8
050
4
$a
QA315-316
050
4
$a
QA402.3
072
7
$a
PBKQ
$2
bicssc
072
7
$a
MAT005000
$2
bisacsh
072
7
$a
PBKQ
$2
thema
072
7
$a
PBU
$2
thema
082
0 4
$a
515.64
$2
23
245
1 0
$a
Advances in Data Science
$h
[electronic resource] /
$c
edited by Ilke Demir, Yifei Lou, Xu Wang, Kathrin Welker.
250
$a
1st ed. 2021.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
XX, 364 p. 185 illus., 166 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
Association for Women in Mathematics Series,
$x
2364-5741 ;
$v
26
505
0
$a
Part I: Image Processing -- Two-stage Geometric Information Guided Image Processing (J. Qin and W. Guo) -- Image Edge Sharpening via Heaviside Substitution and Structure Recovery (L. Deng, W. Guo, and T. Huang) -- Two-step Blind Deconvolution of UPC-A Barcode Images (B. Kim and Y. Lou) -- Part II: Shape and Geometry -- An Anisotropic Local Method for Boundary Detection in Images (M. Lund, M. Howard, D. Wu, R. S. Crum, D. J. Miller, and M. C. Akin) -- Towards Learning Geometric Shape Parts (A. Fondevilla, G. Morin, and K. Leonard) -- Machine Learning in LiDAR 3D Point Clouds (F. P. Medina and R. Paffenroth) -- Part III: Machine Learning -- Fitting Small Piece-wise Linear Neural Network Models to Interpolate Data Sets (L. Ness) -- On Large-Scale Dynamic Topic Modelling with Nonnegative CP Tensor Decomposition (M. Ahn, N. Eikmeier, J. Haddock, L. Kassab, A. Kryshchenko, K. Leonard, D. Needell, R. W. M. A. Madushani, E. Sizikova, and C. Wang) -- A Simple Recovery Framework for Signals with Time-Varying Sparse Support (N. Durgin, R. Grotheer, C. Huang, S. Li, A. Ma, D. Needell, and J. Qin) -- Part IV: Data Analysis -- Role Detection and Prediction in Dynamic Political Networks (E. Evans, W. Guo, A. Genctav, S. Tari, C. Domeniconi, A. Murillo, J. Chuang, L. AlSumait, P. Mani, and N. Youssry) -- Classifying Sleep States Using Persistent Homology and Markov Chains: A Pilot Study (S. Tymochko, K. Singhal, and G. Heo) -- A Survey of Statistical Learning Techniques as Applied to Inexpensive Pediatric Obstructive Sleep Apnea Data (E. T. Winn, M. Vazquez, P. Loliencar, K. Taipale, X. Wang, and G. Heo) -- Nonparametric Estimation of Blood Alcohol Concentration from Transdermal Alcohol Measurements Using Alcohol Biosensor Devices (A. Kryshchenko, M. Sirlanci, and B. Vader).
520
$a
This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals. The contributions are based on discussions from two workshops under Association for Women in Mathematics (AWM), namely the second Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place between July 29 and August 2, 2019 at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, and the third Women in Shape (WiSh) Research Collaboration Workshop that took place between July 16 and 20, 2018 at Trier University in Robert-Schuman-Haus, Trier, Germany. These submissions, seeded by working groups at the conference, form a valuable source for readers who are interested in ideas and methods developed in interdisciplinary research fields. The book features ideas, methods, and tools developed through a broad range of domains, ranging from theoretical analysis on graph neural networks to applications in health science. It also presents original results tackling real-world problems that often involve complex data analysis on large multi-modal data sources.
650
2 4
$a
Probability and Statistics in Computer Science.
$3
669886
650
2 4
$a
Image Processing and Computer Vision.
$3
670819
650
2 4
$a
Mathematical Applications in Computer Science.
$3
815331
650
2 4
$a
Numerical Analysis.
$3
671433
650
2 4
$a
Probability Theory and Stochastic Processes.
$3
593945
650
1 4
$a
Calculus of Variations and Optimal Control; Optimization.
$3
593942
650
0
$a
Mathematical statistics.
$3
527941
650
0
$a
Optical data processing.
$3
639187
650
0
$a
Computer mathematics.
$3
1199796
650
0
$a
Computer science—Mathematics.
$3
1253519
650
0
$a
Numerical analysis.
$3
527939
650
0
$a
Probabilities.
$3
527847
650
0
$a
Calculus of variations.
$3
527927
700
1
$a
Welker, Kathrin.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1362970
700
1
$a
Wang, Xu.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1029438
700
1
$a
Lou, Yifei.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1362969
700
1
$a
Demir, Ilke.
$e
editor.
$4
edt
$4
http://id.loc.gov/vocabulary/relators/edt
$3
1362968
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030798901
776
0 8
$i
Printed edition:
$z
9783030798925
776
0 8
$i
Printed edition:
$z
9783030798932
830
0
$a
Association for Women in Mathematics Series,
$x
2364-5733 ;
$v
1
$3
1260936
856
4 0
$u
https://doi.org/10.1007/978-3-030-79891-8
912
$a
ZDB-2-SMA
912
$a
ZDB-2-SXMS
950
$a
Mathematics and Statistics (SpringerNature-11649)
950
$a
Mathematics and Statistics (R0) (SpringerNature-43713)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入