{"id":"https://openalex.org/W2134155547","doi":"https://doi.org/10.1109/cidm.2013.6597211","title":"Regularization and improved interpretation of linear data mappings and adaptive distance measures","display_name":"Regularization and improved interpretation of linear data mappings and adaptive distance measures","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2134155547","doi":"https://doi.org/10.1109/cidm.2013.6597211","mag":"2134155547"},"language":"en","primary_location":{"id":"doi:10.1109/cidm.2013.6597211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2013.6597211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.rug.nl/en/publications/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022187353","display_name":"Marc Strickert","orcid":null},"institutions":[{"id":"https://openalex.org/I161103922","display_name":"Philipps University of Marburg","ror":"https://ror.org/01rdrb571","country_code":"DE","type":"education","lineage":["https://openalex.org/I161103922"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marc Strickert","raw_affiliation_strings":["Computational Intelligence, Philipps University of Marburg, Germany","[Computational Intelligence, Philipps Universit\u00e4t, Marburg, DE]"],"affiliations":[{"raw_affiliation_string":"Computational Intelligence, Philipps University of Marburg, Germany","institution_ids":["https://openalex.org/I161103922"]},{"raw_affiliation_string":"[Computational Intelligence, Philipps Universit\u00e4t, Marburg, DE]","institution_ids":["https://openalex.org/I161103922"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091180862","display_name":"Barbara Hammer","orcid":"https://orcid.org/0000-0002-0935-5591"},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Barbara Hammer","raw_affiliation_strings":["CITEC centre of excellence, Bielefeld University, Germany","Univ Bielefeld, University of Bielefeld, Fac Technol, CITEC"],"affiliations":[{"raw_affiliation_string":"CITEC centre of excellence, Bielefeld University, Germany","institution_ids":["https://openalex.org/I20121455"]},{"raw_affiliation_string":"Univ Bielefeld, University of Bielefeld, Fac Technol, CITEC","institution_ids":["https://openalex.org/I20121455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027248793","display_name":"Thomas Villmann","orcid":"https://orcid.org/0000-0001-6725-0141"},"institutions":[{"id":"https://openalex.org/I116397343","display_name":"Hochschule Mittweida","ror":"https://ror.org/024ga3r86","country_code":"DE","type":"education","lineage":["https://openalex.org/I116397343"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Villmann","raw_affiliation_strings":["Computer Intelligence Group, University of Applied Sciences Mittweida, Germany","Univ Appl Sci Mittweida, Computat Intelligence Grp"],"affiliations":[{"raw_affiliation_string":"Computer Intelligence Group, University of Applied Sciences Mittweida, Germany","institution_ids":["https://openalex.org/I116397343"]},{"raw_affiliation_string":"Univ Appl Sci Mittweida, Computat Intelligence Grp","institution_ids":["https://openalex.org/I116397343"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083548477","display_name":"Michael Biehl","orcid":"https://orcid.org/0000-0001-5148-4568"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Michael Biehl","raw_affiliation_strings":["Intelligent Systems Group, University of Groningen, Netherlands","Intelligent Systems"],"affiliations":[{"raw_affiliation_string":"Intelligent Systems Group, University of Groningen, Netherlands","institution_ids":["https://openalex.org/I169381384"]},{"raw_affiliation_string":"Intelligent Systems","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022187353"],"corresponding_institution_ids":["https://openalex.org/I161103922"],"apc_list":null,"apc_paid":null,"fwci":5.4367,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95610846,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"58","issue":null,"first_page":"10","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"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/T10057","display_name":"Face and Expression Recognition","score":0.9902999997138977,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9884999990463257,"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/interpretability","display_name":"Interpretability","score":0.9317543506622314},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6516181230545044},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6468807458877563},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.5186021327972412},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.5018537044525146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49061670899391174},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4854462742805481},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48115813732147217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45596641302108765},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.43868446350097656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4287436902523041},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3598422706127167},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2731419503688812}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9317543506622314},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6516181230545044},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6468807458877563},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.5186021327972412},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.5018537044525146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49061670899391174},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4854462742805481},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48115813732147217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45596641302108765},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.43868446350097656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4287436902523041},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3598422706127167},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2731419503688812},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/cidm.2013.6597211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cidm.2013.6597211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.rug.nl:openaire/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Strickert, M, Hammer, B, Villmann, T & Biehl, M 2013, Regularization and improved interpretation of linear data mappings and adaptive distance measures. in Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on. IEEE (The Institute of Electrical and Electronics Engineers), pp. 10-17. https://doi.org/10.1109/CIDM.2013.6597211","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.rug.nl:openaire_cris_publications/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","is_oa":true,"landing_page_url":"https://hdl.handle.net/11370/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","pdf_url":"https://pure.rug.nl/ws/files/2340261/2013ProcCIDMStrickert.pdf","source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Strickert, M, Hammer, B, Villmann, T & Biehl, M 2013, Regularization and improved interpretation of linear data mappings and adaptive distance measures. in Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on. IEEE (The Institute of Electrical and Electronics Engineers), pp. 10-17. https://doi.org/10.1109/CIDM.2013.6597211","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pub.librecat.org:2909358","is_oa":false,"landing_page_url":"https://pub.uni-bielefeld.de/record/2909358","pdf_url":null,"source":{"id":"https://openalex.org/S4306401671","display_name":"PUB \u2013 Publications at Bielefeld University (Bielefeld University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20121455","host_organization_name":"Bielefeld University","host_organization_lineage":["https://openalex.org/I20121455"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Strickert M, Hammer B, Villmann T, Biehl M. Regularization and Improved Interpretation of Linear Data Mappings and Adaptive Distance Measures. In:  &lt;em&gt;IEEE SSCI CIDM 2013&lt;/em&gt;. IEEE Computational Intelligence Society;  2013: 10-17.","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:pub.uni-bielefeld.de:2982104","is_oa":false,"landing_page_url":"https://pub.uni-bielefeld.de/record/2982104","pdf_url":null,"source":{"id":"https://openalex.org/S4306401670","display_name":"PUB \u2013 Publications at Bielefeld University (Bielefeld University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20121455","host_organization_name":"Bielefeld University","host_organization_lineage":["https://openalex.org/I20121455"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"http://purl.org/coar/resource_type/c_5794"}],"best_oa_location":{"id":"pmh:oai:pure.rug.nl:openaire/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/911e4c1a-3232-4b11-9eee-cd9f8005fd5d","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Strickert, M, Hammer, B, Villmann, T & Biehl, M 2013, Regularization and improved interpretation of linear data mappings and adaptive distance measures. in Computational Intelligence and Data Mining (CIDM), 2013 IEEE Symposium on. IEEE (The Institute of Electrical and Electronics Engineers), pp. 10-17. https://doi.org/10.1109/CIDM.2013.6597211","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7797691000","display_name":null,"funder_award_id":"HA2719/6-1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G8036144639","display_name":null,"funder_award_id":"CITEC","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W814282759","https://openalex.org/W1509461608","https://openalex.org/W1537462412","https://openalex.org/W1742512077","https://openalex.org/W1984319064","https://openalex.org/W1991016861","https://openalex.org/W2028699682","https://openalex.org/W2035187556","https://openalex.org/W2039434802","https://openalex.org/W2058318567","https://openalex.org/W2081557347","https://openalex.org/W2094150678","https://openalex.org/W2098969718","https://openalex.org/W2099424509","https://openalex.org/W2103595817","https://openalex.org/W2106053110","https://openalex.org/W2108001745","https://openalex.org/W2116731705","https://openalex.org/W2119479037","https://openalex.org/W2123649031","https://openalex.org/W2124067153","https://openalex.org/W2135046866","https://openalex.org/W2136430839","https://openalex.org/W2137570937","https://openalex.org/W2146444479","https://openalex.org/W2148214025","https://openalex.org/W2161764724","https://openalex.org/W2184197540","https://openalex.org/W2399386770","https://openalex.org/W2403017640","https://openalex.org/W3021359550","https://openalex.org/W3151971511","https://openalex.org/W4239741347","https://openalex.org/W4285719527","https://openalex.org/W6675751002","https://openalex.org/W6675960478","https://openalex.org/W6677205618","https://openalex.org/W6712387472","https://openalex.org/W6712881022","https://openalex.org/W7001912067"],"related_works":["https://openalex.org/W2066625485","https://openalex.org/W2948972913","https://openalex.org/W160673860","https://openalex.org/W4289766121","https://openalex.org/W2963642612","https://openalex.org/W4289548080","https://openalex.org/W1585680390","https://openalex.org/W3173587717","https://openalex.org/W4285322112","https://openalex.org/W3165456129"],"abstract_inverted_index":{"Linear":[0],"data":[1,22,29,89],"transformations":[2,32,78],"are":[3,33],"essential":[4],"operations":[5],"in":[6,111,119],"many":[7],"machine":[8,121],"learning":[9,122],"algorithms,":[10],"helping":[11],"to":[12,19,57,62,108],"make":[13,58],"such":[14],"models":[15],"more":[16,65],"flexible":[17],"or":[18],"emphasize":[20],"certain":[21],"directions.":[23],"In":[24,70],"particular":[25],"for":[26,67,85],"high":[27],"dimensional":[28],"sets":[30],"linear":[31,82],"not":[34,45],"necessarily":[35],"uniquely":[36],"determined,":[37],"though,":[38],"and":[39,64,91,114],"alternative":[40],"parameterizations":[41],"exist":[42],"which":[43,79],"do":[44],"change":[46],"the":[47,50,59,68,75,94,97,100,117],"mapping":[48,83],"of":[49,77,99],"training":[51],"data.":[52],"Thus,":[53],"regularization":[54,106],"is":[55],"required":[56],"model":[60],"robust":[61],"noise":[63],"interpretable":[66],"user.":[69],"this":[71],"contribution,":[72],"we":[73,92,115],"characterize":[74],"group":[76],"leave":[80],"a":[81,86],"invariant":[84],"given":[87],"finite":[88],"set,":[90],"discuss":[93],"consequences":[95],"on":[96],"interpretability":[98],"models.":[101,123],"We":[102],"propose":[103],"an":[104],"intuitive":[105],"mechanism":[107],"avoid":[109],"problems":[110],"under-determined":[112],"configurations,":[113],"test":[116],"approach":[118],"two":[120]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
