{"id":"https://openalex.org/W2945259587","doi":"https://doi.org/10.1109/icpr48806.2021.9412779","title":"Locality-Promoting Representation Learning","display_name":"Locality-Promoting Representation Learning","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W2945259587","doi":"https://doi.org/10.1109/icpr48806.2021.9412779","mag":"2945259587"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.10661","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101711824","display_name":"Johannes Schneider","orcid":"https://orcid.org/0000-0002-3225-5564"},"institutions":[{"id":"https://openalex.org/I184656255","display_name":"University of Liechtenstein","ror":"https://ror.org/01qjrx392","country_code":"LI","type":"education","lineage":["https://openalex.org/I184656255"]}],"countries":["LI"],"is_corresponding":true,"raw_author_name":"Johannes Schneider","raw_affiliation_strings":["Institute of Information Systems, University of Liechtenstein, Vaduz, Liechtenstein","Institute of Information Systems, University of Liechtenstein,Vaduz,Liechtenstein"],"affiliations":[{"raw_affiliation_string":"Institute of Information Systems, University of Liechtenstein, Vaduz, Liechtenstein","institution_ids":["https://openalex.org/I184656255"]},{"raw_affiliation_string":"Institute of Information Systems, University of Liechtenstein,Vaduz,Liechtenstein","institution_ids":["https://openalex.org/I184656255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101711824"],"corresponding_institution_ids":["https://openalex.org/I184656255"],"apc_list":null,"apc_paid":null,"fwci":0.1398,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50890114,"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":"8061","last_page":"8068"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.923062801361084},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.6884923577308655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6651724576950073},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6586195230484009},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6075196862220764},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5612615346908569},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5410619378089905},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46092531085014343},{"id":"https://openalex.org/keywords/cohesion","display_name":"Cohesion (chemistry)","score":0.43209266662597656},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42008885741233826},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4019915461540222}],"concepts":[{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.923062801361084},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.6884923577308655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6651724576950073},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6586195230484009},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6075196862220764},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5612615346908569},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5410619378089905},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46092531085014343},{"id":"https://openalex.org/C104054115","wikidata":"https://www.wikidata.org/wiki/Q216828","display_name":"Cohesion (chemistry)","level":2,"score":0.43209266662597656},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42008885741233826},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4019915461540222},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.10661","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.10661","pdf_url":"https://arxiv.org/pdf/1905.10661","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"},{"id":"mag:2945259587","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1905.10661v3","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1905.10661","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1905.10661","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1905.10661","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.10661","pdf_url":"https://arxiv.org/pdf/1905.10661","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":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2945259587.pdf","grobid_xml":"https://content.openalex.org/works/W2945259587.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W603908379","https://openalex.org/W1489108128","https://openalex.org/W1563795667","https://openalex.org/W1686810756","https://openalex.org/W1902934009","https://openalex.org/W1918100026","https://openalex.org/W1967925781","https://openalex.org/W2097117768","https://openalex.org/W2105464770","https://openalex.org/W2118858186","https://openalex.org/W2122825543","https://openalex.org/W2123045220","https://openalex.org/W2133319764","https://openalex.org/W2161176300","https://openalex.org/W2163922914","https://openalex.org/W2194775991","https://openalex.org/W2279221249","https://openalex.org/W2467514673","https://openalex.org/W2515385951","https://openalex.org/W2531409750","https://openalex.org/W2553902701","https://openalex.org/W2612445135","https://openalex.org/W2750384547","https://openalex.org/W2753024126","https://openalex.org/W2788715907","https://openalex.org/W2789062658","https://openalex.org/W2890715498","https://openalex.org/W2950577311","https://openalex.org/W2962953743","https://openalex.org/W2963305465","https://openalex.org/W2981609437","https://openalex.org/W2982536526","https://openalex.org/W3118608800","https://openalex.org/W6600213771","https://openalex.org/W6618372016","https://openalex.org/W6636510571","https://openalex.org/W6637373629","https://openalex.org/W6677995690","https://openalex.org/W6694954494","https://openalex.org/W6743853957","https://openalex.org/W6748025267","https://openalex.org/W6748570084"],"related_works":["https://openalex.org/W2262208379","https://openalex.org/W2768708362","https://openalex.org/W2750881831","https://openalex.org/W3125831646","https://openalex.org/W3169315049","https://openalex.org/W3104618597","https://openalex.org/W3198843987","https://openalex.org/W2916117399","https://openalex.org/W2986368801","https://openalex.org/W2795414739","https://openalex.org/W189527201","https://openalex.org/W2683470288","https://openalex.org/W2962887459","https://openalex.org/W2278701870","https://openalex.org/W3035435178","https://openalex.org/W2554460311","https://openalex.org/W3135119215","https://openalex.org/W3083880329","https://openalex.org/W3122263332","https://openalex.org/W3132072091"],"abstract_inverted_index":{"This":[0],"work":[1],"investigates":[2],"questions":[3],"related":[4],"to":[5],"learning":[6],"features":[7],"in":[8],"convolutional":[9],"neural":[10],"networks":[11],"(CNN).":[12],"Empirical":[13],"findings":[14],"across":[15,56],"multiple":[16,57],"architectures":[17,58],"such":[18],"as":[19],"VGG,":[20],"ResNet,":[21],"Inception":[22],"and":[23,59],"MobileNet":[24],"indicate":[25],"that":[26,65],"weights":[27,37],"near":[28],"the":[29,39,66,77],"center":[30],"of":[31,79],"a":[32],"filter":[33],"are":[34],"larger":[35],"than":[36],"on":[38],"outside.":[40],"Current":[41],"regularization":[42],"schemes":[43],"violate":[44],"this":[45],"principle.":[46],"Thus,":[47],"we":[48],"introduce":[49],"Locality-promoting":[50],"Regularization,":[51],"which":[52],"yields":[53],"accuracy":[54],"gains":[55],"datasets.":[60],"We":[61],"also":[62],"show":[63],"theoretically":[64],"empirical":[67],"finding":[68],"could":[69],"be":[70],"explained":[71],"by":[72],"maximizing":[73],"feature":[74],"cohesion":[75],"under":[76],"assumption":[78],"spatial":[80],"locality.":[81]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}