Linear-size approximations to the vietoris-rips filtration

The Vietoris–Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add topological structure to an otherwise disconnected set of points. It is widely used because it encodes useful information about the topology of the u...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Discrete & computational geometry s. 778 - 796
Hlavní autor: Sheehy, Donald
Médium: Journal Article
Jazyk:angličtina
Vydáno: Springer Verlag 2013
Témata:
ISSN:0179-5376, 1432-0444
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract The Vietoris–Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add topological structure to an otherwise disconnected set of points. It is widely used because it encodes useful information about the topology of the underlying metric space. This information is of-ten extracted from its so-called persistence diagram. Unfortunately, this filtration is often too large to construct in full. We show how to construct an O(n)-size filtered simplicial complex on an n-point metric space such that its persistence diagram is a good approximation to that of the Vietoris–Rips filtration. This new filtration can be constructed in O(n log n) time. The constant factors in both the size and the run-ning time depend only on the doubling dimension of the metric space and the desired tightness of the approximation. For the first time, this makes it computationally tractable to approximate the persistence di-agram of the Vietoris–Rips filtration across all scales for large data sets. We describe two different sparse filtrations. The first is a zigzag filtration that removes points as the scale increases. The second is a (non-zigzag) filtration that yields the same persistence diagram. Both methods are based on a hierarchical net-tree and yield the same guar-antees. La filtration de Vietoris-Rips est un outil très versatile en analyse topologique des données. C'est une séquence de complexes simpliciaux construits sur une métrique pour ajouter de la structure topologique à un nuage de points. Malheureusement, cette filtration est souvent trop large pour tenir entièerement en mémoire. Nous montrons comment construire un complexe simplicial filtré de taille O(n) à partir d'un espace métrique fini composé de n points, de manièere à ce que le diagramme de persistance de ce complexe filtré soit une bonne approximation de celui de la filtration de Vietoris-Rips.
AbstractList The Vietoris–Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add topological structure to an otherwise disconnected set of points. It is widely used because it encodes useful information about the topology of the underlying metric space. This information is of-ten extracted from its so-called persistence diagram. Unfortunately, this filtration is often too large to construct in full. We show how to construct an O(n)-size filtered simplicial complex on an n-point metric space such that its persistence diagram is a good approximation to that of the Vietoris–Rips filtration. This new filtration can be constructed in O(n log n) time. The constant factors in both the size and the run-ning time depend only on the doubling dimension of the metric space and the desired tightness of the approximation. For the first time, this makes it computationally tractable to approximate the persistence di-agram of the Vietoris–Rips filtration across all scales for large data sets. We describe two different sparse filtrations. The first is a zigzag filtration that removes points as the scale increases. The second is a (non-zigzag) filtration that yields the same persistence diagram. Both methods are based on a hierarchical net-tree and yield the same guar-antees. La filtration de Vietoris-Rips est un outil très versatile en analyse topologique des données. C'est une séquence de complexes simpliciaux construits sur une métrique pour ajouter de la structure topologique à un nuage de points. Malheureusement, cette filtration est souvent trop large pour tenir entièerement en mémoire. Nous montrons comment construire un complexe simplicial filtré de taille O(n) à partir d'un espace métrique fini composé de n points, de manièere à ce que le diagramme de persistance de ce complexe filtré soit une bonne approximation de celui de la filtration de Vietoris-Rips.
Author Sheehy, Donald
Author_xml – sequence: 1
  givenname: Donald
  surname: Sheehy
  fullname: Sheehy, Donald
  organization: Geometric computing
BackLink https://inria.hal.science/hal-01111878$$DView record in HAL
BookMark eNotjsFLwzAYxYNMsJuevfbqITNfmqT5vI2hm1Dwsp1L2qQsUpuSlKH-9dbpuzzej8fjLcliCIMj5B7YGkDIR84VcMnWF9fqimQgCk6ZEGJBMgYlUlmU6oYsU3pnjAlkOiNPlR-ciTT5b5ebcYzh03-YyYch5VPIp5PLz95NIfpEox9T3vl-ipfCLbnuTJ_c3b-vyPHl-bDd0-pt97rdVNRwKBVtHTjspJQaDEhp52CFwgZ4J7DhTYvalq61BrmyjeBoZo44N5ALy02xIg9_uyfT12Oc78WvOhhf7zdV_csYzNKlPkPxA7DVTUA
ContentType Journal Article
Copyright Distributed under a Creative Commons Attribution 4.0 International License
Copyright_xml – notice: Distributed under a Creative Commons Attribution 4.0 International License
DBID 1XC
VOOES
DOI 10.1145/2261250.2261286
DatabaseName Hyper Article en Ligne (HAL)
Hyper Article en Ligne (HAL) (Open Access)
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Mathematics
Computer Science
EISSN 1432-0444
EndPage 796
ExternalDocumentID oai:HAL:hal-01111878v1
GroupedDBID -DZ
-Y2
-~C
-~X
.4S
.86
.DC
06D
0R~
0VY
199
1N0
1SB
1XC
203
28-
29G
2J2
2JN
2JY
2KG
2KM
2LR
2P1
2VQ
2WC
2~H
30V
4.4
406
408
409
40D
40E
5GY
5QI
5VS
67Z
692
6NX
78A
88I
8AO
8FE
8FG
8FW
8G5
8TC
8UJ
95-
95.
95~
96X
AABHQ
AACDK
AAGAY
AAHNG
AAIAL
AAJBT
AAJKR
AAKPC
AANZL
AAPKM
AARHV
AARTL
AASML
AATNV
AATVU
AAUYE
AAWCG
AAYIU
AAYQN
AAYTO
ABAKF
ABBBX
ABBRH
ABBXA
ABDBE
ABDZT
ABECU
ABFSG
ABFTV
ABHLI
ABHQN
ABJCF
ABJNI
ABJOX
ABKCH
ABKTR
ABMNI
ABMQK
ABNWP
ABQBU
ABQSL
ABRTQ
ABSXP
ABTEG
ABTHY
ABTKH
ABTMW
ABULA
ABUWG
ABWNU
ABXPI
ACAOD
ACBXY
ACDTI
ACGFS
ACGOD
ACHSB
ACHXU
ACIHN
ACIPV
ACIWK
ACKNC
ACMDZ
ACMLO
ACOKC
ACOMO
ACPIV
ACREN
ACSTC
ACZOJ
ADHHG
ADHIR
ADHKG
ADIMF
ADKNI
ADKPE
ADRFC
ADTPH
ADURQ
ADYFF
ADYOE
ADZKW
AEAQA
AEBTG
AEFIE
AEFQL
AEGAL
AEGNC
AEJHL
AEJRE
AEKMD
AEMSY
AENEX
AEOHA
AEPYU
AESKC
AETLH
AEVLU
AEXYK
AEZWR
AFBBN
AFDZB
AFEXP
AFGCZ
AFHIU
AFKRA
AFLOW
AFOHR
AFQWF
AFWTZ
AFYQB
AFZKB
AGAYW
AGDGC
AGGDS
AGJBK
AGMZJ
AGQEE
AGQMX
AGQPQ
AGRTI
AGWIL
AGWZB
AGYKE
AHAVH
AHBYD
AHKAY
AHPBZ
AHSBF
AHWEU
AHYZX
AI.
AIAKS
AIGIU
AIIXL
AILAN
AITGF
AIXLP
AJBLW
AJRNO
AJZVZ
ALMA_UNASSIGNED_HOLDINGS
ALWAN
AMKLP
AMTXH
AMVHM
AMXSW
AMYLF
AMYQR
AOCGG
ARAPS
ARCSS
ARMRJ
ASPBG
ATHPR
AVWKF
AXYYD
AYFIA
AYJHY
AZFZN
AZQEC
B-.
BA0
BAPOH
BBWZM
BDATZ
BENPR
BGLVJ
BGNMA
BPHCQ
BSONS
C1A
CAG
CCPQU
COF
CS3
CSCUP
DDRTE
DL5
DNIVK
DPUIP
DU5
DWQXO
EBD
EBLON
EBS
EDO
EIOEI
EJD
ESBYG
FEDTE
FERAY
FFXSO
FIGPU
FINBP
FNLPD
FRRFC
FSGXE
FWDCC
GGCAI
GGRSB
GJIRD
GNUQQ
GNWQR
GQ7
GQ8
GUQSH
GXS
H13
HCIFZ
HF~
HG5
HG6
HMJXF
HQYDN
HRMNR
HVGLF
HZ~
I-F
I09
IHE
IJ-
IKXTQ
ITM
IWAJR
IXC
IZIGR
IZQ
I~X
I~Z
J-C
J0Z
JBSCW
JCJTX
JZLTJ
K6V
K7-
KDC
KOV
KOW
KQ8
L6V
LAS
LLZTM
LO0
M2O
M2P
M4Y
M7S
MA-
MQGED
N2Q
N9A
NB0
NDZJH
NPVJJ
NQJWS
NU0
O9-
O93
O9G
O9I
O9J
OAM
OK1
P19
P62
P9R
PADUT
PF0
PHGZM
PHGZT
PQGLB
PQQKQ
PROAC
PT4
PT5
PTHSS
Q2X
QOK
QOS
R4E
R89
R9I
REI
RHV
RNI
RNS
ROL
RPX
RSV
RZK
S16
S1Z
S26
S27
S28
S3B
SAP
SCLPG
SDD
SDH
SHX
SISQX
SJYHP
SMT
SNE
SNPRN
SNX
SOHCF
SOJ
SPISZ
SRMVM
SSLCW
STPWE
SZN
T13
T16
TN5
TSG
TSK
TSV
TUC
TUS
U2A
UG4
UOJIU
UTJUX
UZXMN
VC2
VFIZW
VH1
VOOES
W23
W48
WK8
YLTOR
Z45
ZMTXR
ZWQNP
~EX
ID FETCH-LOGICAL-a2176-ce1e9f55581a155de9fd469b12f49b2bc98d7ecda926db429af499969b924d2a3
ISSN 0179-5376
IngestDate Tue Oct 14 20:28:10 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Language English
License Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-a2176-ce1e9f55581a155de9fd469b12f49b2bc98d7ecda926db429af499969b924d2a3
OpenAccessLink https://inria.hal.science/hal-01111878
PageCount 19
ParticipantIDs hal_primary_oai_HAL_hal_01111878v1
PublicationCentury 2000
PublicationDate 2013
PublicationDateYYYYMMDD 2013-01-01
PublicationDate_xml – year: 2013
  text: 2013
PublicationDecade 2010
PublicationTitle Discrete & computational geometry
PublicationYear 2013
Publisher Springer Verlag
Publisher_xml – name: Springer Verlag
SSID ssj0004908
Score 2.0629203
Snippet The Vietoris–Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add...
SourceID hal
SourceType Open Access Repository
StartPage 778
SubjectTerms Computational Geometry
Computer Science
Title Linear-size approximations to the vietoris-rips filtration
URI https://inria.hal.science/hal-01111878
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVPQU
  databaseName: Advanced Technologies & Aerospace Database
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: P5Z
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/hightechjournals
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: K7-
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Engineering Database
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: M7S
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: BENPR
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Research Library
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: M2O
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/pqrl
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Science Database (ProQuest)
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 20171231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: M2P
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/sciencejournals
  providerName: ProQuest
– providerCode: PRVAVX
  databaseName: SpringerLINK Contemporary 1997-Present
  customDbUrl:
  eissn: 1432-0444
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0004908
  issn: 0179-5376
  databaseCode: RSV
  dateStart: 19970101
  isFulltext: true
  titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22
  providerName: Springer Nature
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3PT9swFLamssM4jMGYNthQNHFDHo3rxPFu3QB1WldVwCRukZM4tNJIESmo2l-_zz_apsCBHbg4iRNFib_kvfc92d8jZL8dw-dlPKeqVCWFh4pohsjXUhURFTHiOSvi2heDQXJxIYe-SmdtywmIqkpmM3n9rFCjD2CbpbP_AffipujAPkBHC9jRPgl4sEu8Eq3Hf7VTDJ-Nr_x8Nx9nwhUaaZCawmDURpnJS-c2A9WjMewJAmr7aeS29MM8bXipJ1d6upw-fDbS2mHlEs3NRIJbAbqSQjxopBB9tlFIavRenLNwFpJ3GDUicw2rJ1wVHu9AhStR-9A2cyNjwYxmWdT-YrePqWD3umfp8Ogk7f8Y_Fw925g62Ov20Y7UH9o2Nj8RyR0o8BoT4EctsvbteDA8XS6PlbYw4eJtvMITnufw3tMgwBjNE-o2wDh_Q157ZhB0HaKb5IWutsjGvOpG4I3wFln_tVDard-Srw24g1W4g-kkwJXBCtzBEu5t8vvk-Px7j_p6GFTh94lprkMtSyPQFiqEgQUOCh7LLGQllxnLcpkUQueFkiwuMgQaqrR8VmYg2QVTnXekVU0q_Z4EpeYx43GUhzzjoe7InIcljxTvgEGAMn8gnzEQ6bVTPEmNBjmGPDV9ywHfecpFu-QVsxVETNbqI2lNb271J_Iyv5uO65s9D9U_q69Kbw
linkProvider ProQuest
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Linear-size+approximations+to+the+vietoris-rips+filtration&rft.jtitle=Discrete+%26+computational+geometry&rft.au=Sheehy%2C+Donald&rft.date=2013&rft.pub=Springer+Verlag&rft.issn=0179-5376&rft.eissn=1432-0444&rft.spage=778&rft.epage=796&rft_id=info:doi/10.1145%2F2261250.2261286&rft.externalDBID=HAS_PDF_LINK&rft.externalDocID=oai%3AHAL%3Ahal-01111878v1
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0179-5376&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0179-5376&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0179-5376&client=summon