{"id":"https://openalex.org/W2889084551","doi":"https://doi.org/10.1109/ssp.2018.8450819","title":"Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted \u2113<sub>1</sub> Regularization","display_name":"Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted \u2113<sub>1</sub> Regularization","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2889084551","doi":"https://doi.org/10.1109/ssp.2018.8450819","mag":"2889084551"},"language":"en","primary_location":{"id":"doi:10.1109/ssp.2018.8450819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","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/A5091676855","display_name":"Dejiao Zhang","orcid":null},"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":true,"raw_author_name":"Dejiao Zhang","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066883909","display_name":"Julian Katz-Samuels","orcid":null},"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":"Julian Katz-Samuels","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026826555","display_name":"M\u00e1rio A. T. Figueiredo","orcid":"https://orcid.org/0000-0002-0970-7745"},"institutions":[{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]},{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Mario A.T. Figueiredo","raw_affiliation_strings":["Instituto de Telecomunica\u00e7\u00f5es and Instituto Superior T\u00e9cnico, Universidade de Lisboa, Portugal"],"affiliations":[{"raw_affiliation_string":"Instituto de Telecomunica\u00e7\u00f5es and Instituto Superior T\u00e9cnico, Universidade de Lisboa, Portugal","institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I141596103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029521003","display_name":"Laura Balzano","orcid":"https://orcid.org/0000-0003-2914-123X"},"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":"Laura Balzano","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091676855"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.2027,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50318505,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"69"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T12676","display_name":"Machine Learning and ELM","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/regularization","display_name":"Regularization (linguistics)","score":0.7176001667976379},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6820583939552307},{"id":"https://openalex.org/keywords/tying","display_name":"Tying","score":0.6170063614845276},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5628613233566284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5588558316230774},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.542218029499054},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.511092483997345},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4871971011161804},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4834924340248108},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4387887120246887},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4322543740272522},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4264867305755615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40114015340805054},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3514866828918457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2622257173061371},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13767457008361816}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7176001667976379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6820583939552307},{"id":"https://openalex.org/C2780938662","wikidata":"https://www.wikidata.org/wiki/Q973710","display_name":"Tying","level":2,"score":0.6170063614845276},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5628613233566284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5588558316230774},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.542218029499054},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.511092483997345},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4871971011161804},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4834924340248108},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4387887120246887},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4322543740272522},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4264867305755615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40114015340805054},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3514866828918457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2622257173061371},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13767457008361816},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssp.2018.8450819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp.2018.8450819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1570197553","https://openalex.org/W1724438581","https://openalex.org/W1916786071","https://openalex.org/W1949314668","https://openalex.org/W2012653948","https://openalex.org/W2095705004","https://openalex.org/W2109449402","https://openalex.org/W2112796928","https://openalex.org/W2114766824","https://openalex.org/W2119144962","https://openalex.org/W2122825543","https://openalex.org/W2125389748","https://openalex.org/W2134264591","https://openalex.org/W2145607950","https://openalex.org/W2167215970","https://openalex.org/W2172166488","https://openalex.org/W2259303769","https://openalex.org/W2460144244","https://openalex.org/W2472090958","https://openalex.org/W2555421572","https://openalex.org/W2557283755","https://openalex.org/W2592862485","https://openalex.org/W2787178869","https://openalex.org/W2950248853","https://openalex.org/W2963696951","https://openalex.org/W2964299589","https://openalex.org/W4244393449","https://openalex.org/W4293406386","https://openalex.org/W4293461037","https://openalex.org/W6634294911","https://openalex.org/W6637709462","https://openalex.org/W6674330103","https://openalex.org/W6677103964","https://openalex.org/W6677580257","https://openalex.org/W6678583879","https://openalex.org/W6684563725","https://openalex.org/W6685405536","https://openalex.org/W6692147582","https://openalex.org/W6717994387","https://openalex.org/W6720323505","https://openalex.org/W6729551784","https://openalex.org/W6748323323","https://openalex.org/W6764034911"],"related_works":["https://openalex.org/W2998037107","https://openalex.org/W1569871744","https://openalex.org/W2379437105","https://openalex.org/W2016024526","https://openalex.org/W3139928442","https://openalex.org/W1567336638","https://openalex.org/W3124892642","https://openalex.org/W3125367266","https://openalex.org/W2294590153","https://openalex.org/W4220659530"],"abstract_inverted_index":{"A":[0],"deep":[1,106],"neural":[2],"network":[3,116],"(DNN)":[4],"usually":[5],"contains":[6],"millions":[7],"of":[8,88],"parameters,":[9],"making":[10],"both":[11],"storage":[12],"and":[13],"computation":[14],"extremely":[15],"expensive.":[16],"Although":[17],"this":[18,36],"high":[19],"capacity":[20],"allows":[21],"DNNs":[22],"to":[23,32,80,95],"learn":[24],"sophisticated":[25],"mappings,":[26],"it":[27,111],"also":[28,83],"makes":[29],"them":[30],"prone":[31],"over-fitting.":[33],"To":[34],"tackle":[35],"issue,":[37],"we":[38],"adopt":[39],"a":[40,96],"recently":[41],"proposed":[42],"sparsity-inducing":[43,69],"regularizer":[44,103],"called":[45],"OWL":[46,71,102],"(ordered":[47],"weighted":[48],"\u2113":[49],"<sub":[50],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[51],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[52],",":[53],"which":[54],"has":[55],"proven":[56],"effective":[57],"in":[58],"sparse":[59],"linear":[60],"regression":[61],"with":[62,117],"strongly":[63],"correlated":[64,86],"covariates.":[65],"Unlike":[66],"the":[67,92,101,115],"conventional":[68],"regularizers,":[70],"simultaneously":[72],"eliminates":[73],"unimportant":[74],"variables":[75,89],"by":[76,90],"setting":[77],"their":[78],"weights":[79,94],"zero,":[81],"while":[82],"explicitly":[84],"identifying":[85],"groups":[87],"tying":[91],"corresponding":[93],"common":[97],"value.":[98],"We":[99],"evaluate":[100],"on":[104,123],"several":[105],"learning":[107],"benchmarks,":[108],"showing":[109],"that":[110],"can":[112],"dramatically":[113],"compress":[114],"slight":[118],"or":[119],"even":[120],"no":[121],"loss":[122],"generalization":[124],"accuracy.":[125]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}
