{"id":"https://openalex.org/W2077042258","doi":"https://doi.org/10.1145/2783258.2783391","title":"Structural Graphical Lasso for Learning Mouse Brain Connectivity","display_name":"Structural Graphical Lasso for Learning Mouse Brain Connectivity","publication_year":2015,"publication_date":"2015-08-07","ids":{"openalex":"https://openalex.org/W2077042258","doi":"https://doi.org/10.1145/2783258.2783391","mag":"2077042258"},"language":"en","primary_location":{"id":"doi:10.1145/2783258.2783391","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002854172","display_name":"Sen Yang","orcid":"https://orcid.org/0000-0003-3222-2268"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sen Yang","raw_affiliation_strings":["IDST at Alibaba Group, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"IDST at Alibaba Group, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210095624"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103218833","display_name":"Qian Sun","orcid":"https://orcid.org/0000-0002-2098-9878"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Sun","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA","Arizona State University , Tempe , AZ , USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Arizona State University , Tempe , AZ , USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052278550","display_name":"Shuiwang Ji","orcid":"https://orcid.org/0000-0002-4205-4563"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shuiwang Ji","raw_affiliation_strings":["Old Dominion University, Norfolk, VA, USA","Old Dominion University, Norfolk , VA, USA"],"affiliations":[{"raw_affiliation_string":"Old Dominion University, Norfolk, VA, USA","institution_ids":["https://openalex.org/I81365321"]},{"raw_affiliation_string":"Old Dominion University, Norfolk , VA, USA","institution_ids":["https://openalex.org/I81365321"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076768552","display_name":"Peter Wonka","orcid":"https://orcid.org/0000-0003-0627-9746"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Peter Wonka","raw_affiliation_strings":["King Abdullah University of Science and Technology, Thuwal, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"King Abdullah University of Science and Technology, Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030289182","display_name":"Ian Davidson","orcid":"https://orcid.org/0000-0002-1258-4213"},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ian Davidson","raw_affiliation_strings":["University of California, Davis, CA, USA","[University of California, Davis, CA~, USA]"],"affiliations":[{"raw_affiliation_string":"University of California, Davis, CA, USA","institution_ids":["https://openalex.org/I84218800"]},{"raw_affiliation_string":"[University of California, Davis, CA~, USA]","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010419481","display_name":"Jieping Ye","orcid":"https://orcid.org/0000-0001-8662-5818"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jieping Ye","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5002854172"],"corresponding_institution_ids":["https://openalex.org/I4210095624"],"apc_list":null,"apc_paid":null,"fwci":6.543,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.97011921,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1385","last_page":"1394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.7625246047973633},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7199640870094299},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.6658319234848022},{"id":"https://openalex.org/keywords/elastic-net-regularization","display_name":"Elastic net regularization","score":0.5552032589912415},{"id":"https://openalex.org/keywords/connectome","display_name":"Connectome","score":0.5364573001861572},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5312734842300415},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5159724354743958},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5070590972900391},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.49877381324768066},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4895997643470764},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46941670775413513},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.4448021650314331},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4107198119163513},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3472668528556824},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3465149700641632},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33059972524642944},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18010592460632324},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.1217014491558075},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.12165340781211853}],"concepts":[{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.7625246047973633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7199640870094299},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.6658319234848022},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.5552032589912415},{"id":"https://openalex.org/C45715564","wikidata":"https://www.wikidata.org/wiki/Q1292103","display_name":"Connectome","level":3,"score":0.5364573001861572},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5312734842300415},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5159724354743958},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5070590972900391},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.49877381324768066},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4895997643470764},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46941670775413513},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.4448021650314331},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4107198119163513},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3472668528556824},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3465149700641632},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33059972524642944},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18010592460632324},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.1217014491558075},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.12165340781211853},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2783258.2783391","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2783258.2783391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.kaust.edu.sa:10754/575775","is_oa":false,"landing_page_url":"http://hdl.handle.net/10754/575775","pdf_url":null,"source":{"id":"https://openalex.org/S4306401596","display_name":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71920554","host_organization_name":"King Abdullah University of Science and Technology","host_organization_lineage":["https://openalex.org/I71920554"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W3219084","https://openalex.org/W167498579","https://openalex.org/W1549171236","https://openalex.org/W1566327188","https://openalex.org/W1965626594","https://openalex.org/W1986941254","https://openalex.org/W1995515386","https://openalex.org/W2010824638","https://openalex.org/W2039050532","https://openalex.org/W2053186586","https://openalex.org/W2055400003","https://openalex.org/W2058414375","https://openalex.org/W2061564920","https://openalex.org/W2074360197","https://openalex.org/W2081746825","https://openalex.org/W2093042090","https://openalex.org/W2105760337","https://openalex.org/W2106116051","https://openalex.org/W2106802398","https://openalex.org/W2109907994","https://openalex.org/W2116805437","https://openalex.org/W2126607811","https://openalex.org/W2132555912","https://openalex.org/W2135046866","https://openalex.org/W2138265962","https://openalex.org/W2138382427","https://openalex.org/W2148974830","https://openalex.org/W2151128232","https://openalex.org/W2154947819","https://openalex.org/W2163702333","https://openalex.org/W2163707651","https://openalex.org/W2164278908","https://openalex.org/W2597851033","https://openalex.org/W2606098075","https://openalex.org/W2606211438","https://openalex.org/W2913668833","https://openalex.org/W2949606983","https://openalex.org/W2950215113","https://openalex.org/W3098834468","https://openalex.org/W4292363360","https://openalex.org/W6600126799","https://openalex.org/W6606791906"],"related_works":["https://openalex.org/W2468272465","https://openalex.org/W2429564919","https://openalex.org/W757986597","https://openalex.org/W4212910148","https://openalex.org/W4213314600","https://openalex.org/W4210804200","https://openalex.org/W4399551893","https://openalex.org/W2954774635","https://openalex.org/W4392841950","https://openalex.org/W4285814086"],"abstract_inverted_index":{"Investigations":[0],"into":[1],"brain":[2,9,22,36,59,68,135,157],"connectivity":[3],"aim":[4],"to":[5,30,52,57,91,146,153],"recover":[6],"networks":[7,23,184],"of":[8,21,34,66,74,102,104,111,141,162,169,171,182,219,271],"regions":[10],"connected":[11],"by":[12,16,62,124],"anatomical":[13],"tracts":[14],"or":[15],"functional":[17],"associations.":[18],"The":[19,85,133],"inference":[20],"has":[24,49],"recently":[25],"attracted":[26],"much":[27],"interest":[28],"due":[29],"the":[31,63,67,72,88,108,112,117,127,139,142,148,155,160,167,193,209,216,221,232,237,259,267,272],"increasing":[32],"availability":[33],"high-resolution":[35],"imaging":[37],"data.":[38],"Sparse":[39],"inverse":[40],"covariance":[41],"estimation":[42],"with":[43,79],"lasso":[44,47],"and":[45,236,255,269],"group":[46],"penalty":[48],"been":[50],"demonstrated":[51],"be":[53],"a":[54,76,93,121,198,228],"powerful":[55],"approach":[56],"discover":[58],"networks.":[60],"Motivated":[61],"hierarchical":[64,99],"structure":[65],"networks,":[69],"we":[70,196,242],"consider":[71],"problem":[73],"estimating":[75,183],"graphical":[77,89,151,211],"model":[78,90,152],"tree-structural":[80,149],"regularization":[81,86],"in":[82,97,116,126,208,245],"this":[83,98,246],"paper.":[84,247],"encourages":[87],"exhibit":[92],"brain-like":[94],"structure.":[95],"Specifically,":[96],"structure,":[100],"hundreds":[101,170],"thousands":[103],"voxels":[105,125],"serve":[106],"as":[107,138],"leaf":[109],"nodes":[110],"tree.":[113,143],"A":[114],"node":[115],"intermediate":[118],"layer":[119],"represents":[120],"region":[122],"formed":[123],"subtree":[128],"rooted":[129],"at":[130],"that":[131,179,241],"node.":[132],"whole":[134],"is":[136,225],"considered":[137],"root":[140],"We":[144,248],"propose":[145],"apply":[147],"regularized":[150],"estimate":[154],"mouse":[156],"network.":[158],"However,":[159],"dimensionality":[161],"whole-brain":[163],"data,":[164],"usually":[165],"on":[166,227,231,251],"order":[168],"thousands,":[172],"poses":[173],"significant":[174],"computational":[175,194,217],"challenges.":[176],"Efficient":[177],"algorithms":[178],"are":[180,188],"capable":[181],"from":[185,258],"high-dimensional":[186],"data":[187,254,257],"highly":[189],"desired.":[190],"To":[191],"address":[192],"challenge,":[195],"develop":[197],"screening":[199,235],"rule":[200],"which":[201],"can":[202],"quickly":[203],"identify":[204],"many":[205],"zero":[206],"blocks":[207],"estimated":[210],"model,":[212],"thereby":[213],"dramatically":[214],"reducing":[215],"cost":[218],"solving":[220],"proposed":[222,273],"model.":[223],"It":[224],"based":[226],"novel":[229],"insight":[230],"relationship":[233],"between":[234],"so-called":[238],"proximal":[239],"operator":[240],"first":[243],"establish":[244],"perform":[249],"experiments":[250],"both":[252],"synthetic":[253],"real":[256],"Allen":[260],"Developing":[261],"Mouse":[262],"Brain":[263],"Atlas;":[264],"results":[265],"demonstrate":[266],"effectiveness":[268],"efficiency":[270],"approach.":[274]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}