{"id":"https://openalex.org/W2802960562","doi":"https://doi.org/10.1109/icip.2018.8451092","title":"Shade: Information-Based Regularization for Deep Learning","display_name":"Shade: Information-Based Regularization for Deep Learning","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2802960562","doi":"https://doi.org/10.1109/icip.2018.8451092","mag":"2802960562"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/1804.10988","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112030698","display_name":"Micha\u00ebl Blot","orcid":null},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210159731","display_name":"Laboratoire de Recherche en Informatique de Paris 6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Michael Blot","raw_affiliation_strings":["CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France"],"affiliations":[{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100655598","display_name":"Thomas Robert","orcid":"https://orcid.org/0000-0002-6502-7082"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I4210159731","display_name":"Laboratoire de Recherche en Informatique de Paris 6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Thomas Robert","raw_affiliation_strings":["CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France"],"affiliations":[{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017490804","display_name":"Nicolas Thome","orcid":"https://orcid.org/0000-0003-4871-3045"},"institutions":[{"id":"https://openalex.org/I124158823","display_name":"Conservatoire National des Arts et M\u00e9tiers","ror":"https://ror.org/0175hh227","country_code":"FR","type":"education","lineage":["https://openalex.org/I124158823","https://openalex.org/I4210134562"]},{"id":"https://openalex.org/I4210145724","display_name":"Centre d'Etudes et De Recherche en Informatique et Communications","ror":"https://ror.org/044j5mm75","country_code":"FR","type":"facility","lineage":["https://openalex.org/I4210145724"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Nicolas Thome","raw_affiliation_strings":["CEDRIC, Conservatoire National des Arts et Metiers, Paris, France","CEDRIC, Conservatoire National des Arts et Metiers, 292 Rue St Martin, Paris, F-75003, France"],"affiliations":[{"raw_affiliation_string":"CEDRIC, Conservatoire National des Arts et Metiers, Paris, France","institution_ids":["https://openalex.org/I124158823","https://openalex.org/I4210145724"]},{"raw_affiliation_string":"CEDRIC, Conservatoire National des Arts et Metiers, 292 Rue St Martin, Paris, F-75003, France","institution_ids":["https://openalex.org/I124158823","https://openalex.org/I4210145724"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108118084","display_name":"Matthieu Cord","orcid":"https://orcid.org/0000-0002-0627-5844"},"institutions":[{"id":"https://openalex.org/I4210159731","display_name":"Laboratoire de Recherche en Informatique de Paris 6","ror":"https://ror.org/05krcen59","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159245","https://openalex.org/I4210159731"]},{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Matthieu Cord","raw_affiliation_strings":["CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France"],"affiliations":[{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Paris, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"CNRS, Laboratoire d'Informatique de Paris 6, Sorbonne Universite, LIP6, Paris, F-75005, France","institution_ids":["https://openalex.org/I4210159731","https://openalex.org/I39804081","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112030698"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I39804081","https://openalex.org/I4210159731"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04665355,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"813","last_page":"817"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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":0.9987000226974487,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.998199999332428,"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/regularization","display_name":"Regularization (linguistics)","score":0.7595195770263672},{"id":"https://openalex.org/keywords/conditional-entropy","display_name":"Conditional entropy","score":0.644324779510498},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.6422944068908691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6286910772323608},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6028566956520081},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5253027081489563},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.520026445388794},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4839392304420471},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4597170352935791},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.43632155656814575},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.328788697719574},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.3212919533252716},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3210568130016327}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7595195770263672},{"id":"https://openalex.org/C101721835","wikidata":"https://www.wikidata.org/wiki/Q813908","display_name":"Conditional entropy","level":3,"score":0.644324779510498},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.6422944068908691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6286910772323608},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028566956520081},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5253027081489563},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.520026445388794},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4839392304420471},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4597170352935791},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.43632155656814575},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.328788697719574},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.3212919533252716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3210568130016327},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.1109/icip.2018.8451092","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451092","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1804.10988","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.10988","pdf_url":"https://arxiv.org/pdf/1804.10988","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":"","raw_type":null},{"id":"pmh:oai:arXiv.org:1805.05814","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.05814","pdf_url":"https://arxiv.org/pdf/1805.05814","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":"","raw_type":"text"},{"id":"pmh:oai:HAL:hal-01994740v1","is_oa":true,"landing_page_url":"https://hal.sorbonne-universite.fr/hal-01994740","pdf_url":null,"source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ICIP 2018 - 25th IEEE International Conference on Image Processing, Oct 2018, Ath\u00e8nes, Greece. pp.813-817, ⟨10.1109/ICIP.2018.8451092⟩","raw_type":"Conference papers"},{"id":"doi:10.48550/arxiv.1804.10988","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1804.10988","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"},{"id":"doi:10.48550/arxiv.1805.05814","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1805.05814","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"},{"id":"mag:2802960562","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1804.10988","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1804.10988","pdf_url":"https://arxiv.org/pdf/1804.10988","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":"","raw_type":null},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W4919037","https://openalex.org/W114517082","https://openalex.org/W1686946872","https://openalex.org/W1882958252","https://openalex.org/W1907282891","https://openalex.org/W1959608418","https://openalex.org/W1994906459","https://openalex.org/W2054658115","https://openalex.org/W2063756240","https://openalex.org/W2072072671","https://openalex.org/W2095705004","https://openalex.org/W2099111195","https://openalex.org/W2114771311","https://openalex.org/W2117539524","https://openalex.org/W2123469175","https://openalex.org/W2133319764","https://openalex.org/W2144513243","https://openalex.org/W2194775991","https://openalex.org/W2363000733","https://openalex.org/W2438305798","https://openalex.org/W2510550085","https://openalex.org/W2557579533","https://openalex.org/W2579923771","https://openalex.org/W2617539226","https://openalex.org/W2738853914","https://openalex.org/W2789019380","https://openalex.org/W2809994596","https://openalex.org/W2949117887","https://openalex.org/W2950011704","https://openalex.org/W2963826681","https://openalex.org/W2964059111","https://openalex.org/W2964184826","https://openalex.org/W3118608800","https://openalex.org/W3137695714","https://openalex.org/W6637108112","https://openalex.org/W6638667902","https://openalex.org/W6640963894","https://openalex.org/W6674330103","https://openalex.org/W6681151457","https://openalex.org/W6684191040","https://openalex.org/W6685378274","https://openalex.org/W6718140377","https://openalex.org/W6729906282","https://openalex.org/W6732696085","https://openalex.org/W6739879593","https://openalex.org/W6763485134"],"related_works":["https://openalex.org/W2964093539","https://openalex.org/W3008836981","https://openalex.org/W170527615","https://openalex.org/W1967530176","https://openalex.org/W2998569246","https://openalex.org/W3196069887","https://openalex.org/W2785619321","https://openalex.org/W2893853205","https://openalex.org/W1580443261","https://openalex.org/W3112728147","https://openalex.org/W2889727733","https://openalex.org/W2995097486","https://openalex.org/W2269105128","https://openalex.org/W2099048402","https://openalex.org/W2776412785","https://openalex.org/W1993086160","https://openalex.org/W3171972935","https://openalex.org/W258707964","https://openalex.org/W2921681073","https://openalex.org/W3006345371"],"abstract_inverted_index":{"Regularization":[0],"is":[1,30,67],"a":[2,15,33,70,82],"big":[3],"issue":[4],"for":[5,22],"training":[6,84],"deep":[7,78],"neural":[8],"networks.":[9],"In":[10],"this":[11],"paper,":[12],"we":[13],"propose":[14],"new":[16],"information-theory-based":[17],"regularization":[18,101],"scheme":[19],"named":[20],"SHADE":[21],"SHAnnon":[23],"DEcay.":[24],"The":[25],"originality":[26],"of":[27,44,53,73,91],"the":[28,42,48,51,60,74,89],"approach":[29,93],"to":[31,68,94,99],"define":[32],"prior":[34],"based":[35],"on":[36,103],"conditional":[37],"entropy,":[38],"which":[39],"explicitly":[40],"decouples":[41],"learning":[43,52],"invariant":[45],"representations":[46],"in":[47,59,81],"regularizer":[49,75],"and":[50,57],"correlations":[54],"between":[55],"inputs":[56],"labels":[58],"data":[61],"fitting":[62],"term.":[63],"Our":[64],"second":[65],"contribution":[66],"derive":[69],"stochastic":[71],"version":[72],"compatible":[76],"with":[77],"learning,":[79],"resulting":[80],"tractable":[83],"scheme.":[85],"We":[86],"empirically":[87],"validate":[88],"efficiency":[90],"our":[92],"improve":[95],"classification":[96],"performances":[97],"compared":[98],"common":[100],"schemes":[102],"several":[104],"standard":[105],"architectures.":[106]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}