{"id":"https://openalex.org/W2749718357","doi":"https://doi.org/10.1109/hpec.2017.8091045","title":"Preconditioned spectral clustering for stochastic block partition streaming graph challenge (Preliminary version at arXiv.)","display_name":"Preconditioned spectral clustering for stochastic block partition streaming graph challenge (Preliminary version at arXiv.)","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2749718357","doi":"https://doi.org/10.1109/hpec.2017.8091045","mag":"2749718357"},"language":"en","primary_location":{"id":"doi:10.1109/hpec.2017.8091045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2017.8091045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.07481","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"David Zhuzhunashvili","orcid":null},"institutions":[{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]},{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David Zhuzhunashvili","raw_affiliation_strings":["University of Colorado, Boulder, Colorado"],"affiliations":[{"raw_affiliation_string":"University of Colorado, Boulder, Colorado","institution_ids":["https://openalex.org/I2802236040","https://openalex.org/I188538660"]}]},{"author_position":"last","author":{"id":null,"display_name":"Andrew Knyazev","orcid":null},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Knyazev","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"],"apc_list":null,"apc_paid":null,"fwci":1.0492,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.76206969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.6047999858856201},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5529999732971191},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44130000472068787},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.43799999356269836},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4320000112056732},{"id":"https://openalex.org/keywords/matlab","display_name":"MATLAB","score":0.4316999912261963},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4230000078678131},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.387800008058548},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.36469998955726624}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6047999858856201},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49880000948905945},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4634999930858612},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44130000472068787},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.43799999356269836},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4320000112056732},{"id":"https://openalex.org/C2780365114","wikidata":"https://www.wikidata.org/wiki/Q169478","display_name":"MATLAB","level":2,"score":0.4316999912261963},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4230000078678131},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.413100004196167},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.387800008058548},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37950000166893005},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.36469998955726624},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.35989999771118164},{"id":"https://openalex.org/C48903430","wikidata":"https://www.wikidata.org/wiki/Q491370","display_name":"Graph partition","level":3,"score":0.34610000252723694},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.3337000012397766},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.32659998536109924},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3208000063896179},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C23463724","wikidata":"https://www.wikidata.org/wiki/Q2308831","display_name":"Spectral method","level":2,"score":0.311599999666214},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.28200000524520874},{"id":"https://openalex.org/C187166803","wikidata":"https://www.wikidata.org/wiki/Q2835831","display_name":"Streaming algorithm","level":3,"score":0.2761000096797943},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2669999897480011},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2581999897956848},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.25619998574256897},{"id":"https://openalex.org/C135554599","wikidata":"https://www.wikidata.org/wiki/Q3682206","display_name":"Multiple description coding","level":3,"score":0.2522999942302704}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/hpec.2017.8091045","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec.2017.8091045","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.07481","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.07481","pdf_url":"https://arxiv.org/pdf/1708.07481","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.07481","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.07481","pdf_url":"https://arxiv.org/pdf/1708.07481","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1586414899","https://openalex.org/W1587744656","https://openalex.org/W2045616426","https://openalex.org/W2051142108","https://openalex.org/W2053107666","https://openalex.org/W2107940287","https://openalex.org/W2117686912","https://openalex.org/W2132914434","https://openalex.org/W2611996208","https://openalex.org/W2752751166","https://openalex.org/W6697289498","https://openalex.org/W6727558369","https://openalex.org/W6727977643","https://openalex.org/W6730044639","https://openalex.org/W6732232499","https://openalex.org/W6922689881"],"related_works":[],"abstract_inverted_index":{"Locally":[0],"Optimal":[1],"Block":[2],"Preconditioned":[3],"Conjugate":[4],"Gradient":[5],"(LOBPCG)":[6],"is":[7,118,153,197],"demonstrated":[8],"to":[9,38,62,146,166,175],"efficiently":[10],"solve":[11],"eigenvalue":[12],"problems":[13],"for":[14,42,51,129,170,188,206],"graph":[15,24,115,125],"Laplacians":[16],"that":[17],"appear":[18],"in":[19,33,57,91,133,173,180],"spectral":[20,151],"clustering.":[21],"For":[22,113],"static":[23,85,148],"partitioning,":[25,116],"10-20":[26],"iterations":[27],"of":[28,98,123,141,159,194],"LOBPCG":[29,117,143],"without":[30],"preconditioning":[31],"result":[32],"~10\u00d7":[34],"error":[35],"reduction,":[36],"enough":[37],"achieve":[39],"100%":[40,76],"correctness":[41],"all":[43],"Challenge":[44,84],"datasets":[45],"with":[46,53,87,120,184],"known":[47],"truth":[48],"partitions,":[49],"e.g.,":[50],"graphs":[52,86,169],"5K/.1M":[54],"(50K/1M)":[55],"Vertices/Edges":[56],"2":[58],"(7)":[59,205],"seconds,":[60],"compared":[61,145],"over":[63,215],"5,000":[64],"(30,000)":[65],"seconds":[66,94],"needed":[67],"by":[68],"the":[69,83,105,124,130,139,147,160,168,171,176,185,189,192,212],"baseline":[70],"Python":[71,74],"code.":[72,178],"Our":[73,100,150],"code":[75,103,187],"correctly":[77],"determines":[78],"98":[79],"(160)":[80],"clusters":[81,107,196],"from":[82],"0.5M":[88],"(2M)":[89],"vertices":[90],"270":[92],"(1,700)":[93],"using":[95],"10GB":[96],"(50GB)":[97],"memory.":[99,112],"single-precision":[101],"MATLAB":[102],"calculates":[104],"same":[106],"at":[108,202],"half":[109],"time":[110],"and":[111],"streaming":[114,182],"initiated":[119],"approximate":[121],"eigenvectors":[122],"Laplacian":[126],"already":[127],"computed":[128],"previous":[131],"graph,":[132,191],"many":[134],"cases":[135],"reducing":[136],"2-3":[137],"times":[138],"number":[140],"required":[142],"iterations,":[144],"case.":[149],"clustering":[152],"generic,":[154],"i.e.":[155],"assuming":[156],"nothing":[157],"specific":[158],"block":[161],"model":[162],"or":[163,199],"streaming,":[164,210],"used":[165],"generate":[167],"Challenge,":[172],"contrast":[174],"base":[177,186],"Nevertheless,":[179],"10-stage":[181],"comparison":[183],"5K":[190],"quality":[193],"our":[195],"similar":[198],"better":[200],"starting":[201],"stage":[203],"4":[204],"emerging":[207],"edging":[208],"(snowballing)":[209],"while":[211],"computations":[213],"are":[214],"100-1000":[216],"faster.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2017-08-31T00:00:00"}