{"id":"https://openalex.org/W4238728061","doi":"https://doi.org/10.1109/iccad.2011.6105321","title":"Toward efficient spatial variation decomposition via sparse regression","display_name":"Toward efficient spatial variation decomposition via sparse regression","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W4238728061","doi":"https://doi.org/10.1109/iccad.2011.6105321"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2011.6105321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2011.6105321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","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/A5056311865","display_name":"Wangyang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wangyang Zhang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025878949","display_name":"Karthik Balakrishnan","orcid":"https://orcid.org/0000-0001-8409-227X"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthik Balakrishnan","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353869","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-4510-2436"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066048721","display_name":"Duane S. Boning","orcid":"https://orcid.org/0000-0002-0417-445X"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duane Boning","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008408555","display_name":"Rob A. Rutenbar","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rob Rutenbar","raw_affiliation_strings":["University of Illinois, Urbana-Champaign, Urbana, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056311865"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.7226,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.8520756,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"162","last_page":"169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.7263200283050537},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5736802816390991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5515062808990479},{"id":"https://openalex.org/keywords/uncorrelated","display_name":"Uncorrelated","score":0.5240654945373535},{"id":"https://openalex.org/keywords/process-variation","display_name":"Process variation","score":0.511027455329895},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48059937357902527},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.423242449760437},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.34463274478912354},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3365914821624756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3321990966796875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30463385581970215}],"concepts":[{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.7263200283050537},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5736802816390991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5515062808990479},{"id":"https://openalex.org/C169345407","wikidata":"https://www.wikidata.org/wiki/Q8216221","display_name":"Uncorrelated","level":2,"score":0.5240654945373535},{"id":"https://openalex.org/C93389723","wikidata":"https://www.wikidata.org/wiki/Q7247313","display_name":"Process variation","level":3,"score":0.511027455329895},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48059937357902527},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.423242449760437},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34463274478912354},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3365914821624756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3321990966796875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30463385581970215},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2011.6105321","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2011.6105321","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1530625153","https://openalex.org/W1572287951","https://openalex.org/W1974774078","https://openalex.org/W2063237963","https://openalex.org/W2075621462","https://openalex.org/W2080352925","https://openalex.org/W2097073572","https://openalex.org/W2097897435","https://openalex.org/W2100992121","https://openalex.org/W2108648342","https://openalex.org/W2113394894","https://openalex.org/W2127271355","https://openalex.org/W2139657321","https://openalex.org/W2140362342","https://openalex.org/W4212863985","https://openalex.org/W4243154030","https://openalex.org/W4255991306"],"related_works":["https://openalex.org/W2386430105","https://openalex.org/W2360779366","https://openalex.org/W2356521405","https://openalex.org/W2038534795","https://openalex.org/W2384358604","https://openalex.org/W2137012493","https://openalex.org/W2144722454","https://openalex.org/W2024870084","https://openalex.org/W2959030164","https://openalex.org/W1564147575"],"abstract_inverted_index":{"In":[0],"this":[1,63,86],"paper,":[2],"we":[3],"propose":[4],"a":[5,54,91],"new":[6],"technique":[7,126],"to":[8,31,72,89,146],"accurately":[9,73],"decompose":[10],"process":[11,42],"variation":[12,27,34,52,77,131],"into":[13],"two":[14],"different":[15],"components:":[16],"(1)":[17],"spatially":[18,50,75,129],"correlated":[19,51,76,130],"variation,":[20],"and":[21,45],"(2)":[22],"uncorrelated":[23,79],"random":[24,80],"variation.":[25,81],"Such":[26],"decomposition":[28],"is":[29,70,88,139],"important":[30,83],"identify":[32],"systematic":[33],"patterns":[35,132],"at":[36],"wafer":[37],"and/or":[38],"chip":[39],"level":[40],"for":[41],"modeling,":[43],"control":[44],"diagnosis.":[46],"We":[47],"demonstrate":[48,120],"that":[49,95,121],"carries":[53],"unique":[55],"sparse":[56,67,101,124],"signature":[57],"in":[58],"frequency":[59],"domain.":[60],"Based":[61],"upon":[62],"observation,":[64],"an":[65],"efficient":[66],"regression":[68,102,125],"algorithm":[69,94],"applied":[71],"separate":[74],"from":[78],"An":[82],"contribution":[84],"of":[85,100,106],"paper":[87],"develop":[90],"fast":[92],"numerical":[93],"reduces":[96],"the":[97,109,122],"computational":[98],"time":[99],"by":[103,141],"several":[104],"orders":[105],"magnitude":[107],"over":[108],"traditional":[110,148],"implementation.":[111],"Our":[112],"experimental":[113],"results":[114],"based":[115],"on":[116],"silicon":[117],"measurement":[118],"data":[119],"proposed":[123],"can":[127],"capture":[128],"with":[133],"high":[134],"accuracy.":[135],"The":[136],"estimation":[137],"error":[138],"reduced":[140],"more":[142],"than":[143],"3.5\u00d7":[144],"compared":[145],"other":[147],"methods.":[149]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}