|
|
|
|
LEADER |
00000nam a22000005i 4500 |
001 |
b3286291 |
003 |
MWH |
005 |
20191021231851.0 |
007 |
cr nn 008mamaa |
008 |
100301s2006 gw | s |||| 0|eng d |
020 |
|
|
|a 9783540341383
|
024 |
7 |
|
|a 10.1007/11752790
|2 doi
|
035 |
|
|
|a (DE-He213)978-3-540-34138-3
|
050 |
|
4 |
|a E-Book
|
072 |
|
7 |
|a UMB
|2 bicssc
|
072 |
|
7 |
|a COM051300
|2 bisacsh
|
072 |
|
7 |
|a UMB
|2 thema
|
245 |
1 |
0 |
|a Subspace, Latent Structure and Feature Selection
|h [electronic resource] :
|b Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers /
|c edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor.
|
250 |
|
|
|a 1st ed. 2006.
|
264 |
|
1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2006.
|
300 |
|
|
|a X, 209 p.
|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 Theoretical Computer Science and General Issues ;
|v 3940
|
490 |
1 |
|
|a Springer eBook Collection
|
505 |
0 |
|
|a Invited Contributions -- Discrete Component Analysis -- Overview and Recent Advances in Partial Least Squares -- Random Projection, Margins, Kernels, and Feature-Selection -- Some Aspects of Latent Structure Analysis -- Feature Selection for Dimensionality Reduction -- Contributed Papers -- Auxiliary Variational Information Maximization for Dimensionality Reduction -- Constructing Visual Models with a Latent Space Approach -- Is Feature Selection Still Necessary? -- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data -- Incorporating Constraints and Prior Knowledge into Factorization Algorithms – An Application to 3D Recovery -- A Simple Feature Extraction for High Dimensional Image Representations -- Identifying Feature Relevance Using a Random Forest -- Generalization Bounds for Subspace Selection and Hyperbolic PCA -- Less Biased Measurement of Feature Selection Benefits.
|
590 |
|
|
|a Loaded electronically.
|
590 |
|
|
|a Electronic access restricted to members of the Holy Cross Community.
|
650 |
|
0 |
|a Algorithms.
|
650 |
|
0 |
|a Mathematical statistics.
|
650 |
|
0 |
|a Computers.
|
650 |
|
0 |
|a Artificial intelligence.
|
650 |
|
0 |
|a Optical data processing.
|
650 |
|
0 |
|a Pattern recognition.
|
690 |
|
|
|a Electronic resources (E-books)
|
700 |
1 |
|
|a Saunders, Craig.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
700 |
1 |
|
|a Grobelnik, Marko.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
700 |
1 |
|
|a Gunn, Steve.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
700 |
1 |
|
|a Shawe-Taylor, John.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
710 |
2 |
|
|a SpringerLink (Online service)
|
773 |
0 |
|
|t Springer eBooks
|
830 |
|
0 |
|a Theoretical Computer Science and General Issues ;
|v 3940
|
830 |
|
0 |
|a Springer eBook Collection.
|
856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://doi.org/10.1007/11752790
|3 Click to view e-book
|t 0
|
907 |
|
|
|a .b3286291x
|b 04-18-22
|c 02-26-20
|
998 |
|
|
|a he
|b 02-26-20
|c m
|d @
|e -
|f eng
|g gw
|h 0
|i 1
|
912 |
|
|
|a ZDB-2-SCS
|
912 |
|
|
|a ZDB-2-LNC
|
950 |
|
|
|a Computer Science (Springer-11645)
|
902 |
|
|
|a springer purchased ebooks
|
903 |
|
|
|a SEB-COLL
|
945 |
|
|
|f - -
|g 1
|h 0
|j - -
|k - -
|l he
|o -
|p $0.00
|q -
|r -
|s b
|t 38
|u 0
|v 0
|w 0
|x 0
|y .i21994535
|z 02-26-20
|
999 |
f |
f |
|i 79303aad-7831-5af5-aab1-36d0b6fc2e97
|s f1fb1f28-74c0-5976-bf74-2d0cd746239d
|t 0
|
952 |
f |
f |
|p Online
|a College of the Holy Cross
|b Main Campus
|c E-Resources
|d Online
|t 0
|e E-Book
|h Library of Congress classification
|i Elec File
|