{"id":"https://openalex.org/W2921390629","doi":"https://doi.org/10.5220/0007583403380345","title":"Gradient Descent Analysis: On Visualizing the Training of Deep Neural Networks","display_name":"Gradient Descent Analysis: On Visualizing the Training of Deep Neural Networks","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2921390629","doi":"https://doi.org/10.5220/0007583403380345","mag":"2921390629"},"language":"en","primary_location":{"id":"doi:10.5220/0007583403380345","is_oa":false,"landing_page_url":"https://doi.org/10.5220/0007583403380345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","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/A5010593743","display_name":"Martin Becker","orcid":"https://orcid.org/0000-0002-4249-7671"},"institutions":[{"id":"https://openalex.org/I75356249","display_name":"Hochschule D\u00fcsseldorf University of Applied Sciences","ror":"https://ror.org/00ftx0026","country_code":"DE","type":"education","lineage":["https://openalex.org/I75356249"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Becker","raw_affiliation_strings":["University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I75356249"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033045571","display_name":"Jens Lippel","orcid":"https://orcid.org/0000-0002-6232-7821"},"institutions":[{"id":"https://openalex.org/I75356249","display_name":"Hochschule D\u00fcsseldorf University of Applied Sciences","ror":"https://ror.org/00ftx0026","country_code":"DE","type":"education","lineage":["https://openalex.org/I75356249"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jens Lippel","raw_affiliation_strings":["University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I75356249"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045119893","display_name":"Thomas Zielke","orcid":"https://orcid.org/0000-0003-1319-2286"},"institutions":[{"id":"https://openalex.org/I75356249","display_name":"Hochschule D\u00fcsseldorf University of Applied Sciences","ror":"https://ror.org/00ftx0026","country_code":"DE","type":"education","lineage":["https://openalex.org/I75356249"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Zielke","raw_affiliation_strings":["University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Applied Sciences D\u00fcsseldorf, M\u00fcnsterstr. 156, 40476, D\u00fcsseldorf and Germany, --- Select a Country ---","institution_ids":["https://openalex.org/I75356249"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1017,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40839592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"338","last_page":"345"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9952999949455261,"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/T10320","display_name":"Neural Networks and Applications","score":0.965399980545044,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9406999945640564,"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/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.7748786211013794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7737703919410706},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.7380776405334473},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6197870969772339},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6028619408607483},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5831701755523682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5388332009315491},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5298775434494019},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4811500310897827},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46896636486053467},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4581652283668518},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43909287452697754}],"concepts":[{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.7748786211013794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7737703919410706},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.7380776405334473},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6197870969772339},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6028619408607483},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5831701755523682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5388332009315491},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5298775434494019},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4811500310897827},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46896636486053467},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4581652283668518},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43909287452697754},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0007583403380345","is_oa":false,"landing_page_url":"https://doi.org/10.5220/0007583403380345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications","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":0,"referenced_works":[],"related_works":["https://openalex.org/W4288259399","https://openalex.org/W2969529314","https://openalex.org/W4312206232","https://openalex.org/W2975301014","https://openalex.org/W4206903459","https://openalex.org/W2754816816","https://openalex.org/W4366280654","https://openalex.org/W3160167280","https://openalex.org/W4231621013","https://openalex.org/W4362706668"],"abstract_inverted_index":{"We":[0,85,126],"present":[1,127],"an":[2,36,128],"approach":[3],"to":[4,79],"visualizing":[5],"gradient":[6,41],"descent":[7,42,61],"methods":[8],"and":[9,111],"discuss":[10],"its":[11],"application":[12],"in":[13],"the":[14,60,69,98,109,120],"context":[15],"of":[16,28,38,59,91,101,113,122,148],"deep":[17],"neural":[18],"network":[19],"(DNN)":[20],"training.":[21],"The":[22],"result":[23],"is":[24,66],"a":[25,52,81,114,132,140,145,149],"novel":[26],"type":[27],"training":[29,54,71,74,83],"error":[30,55,72],"curve":[31],"(a)":[32],"that":[33,49,65,130],"allows":[34],"for":[35,119],"exploration":[37,121],"each":[39,58],"individual":[40],"iteration":[43,75],"at":[44],"line":[45],"search":[46],"level;":[47],"(b)":[48],"reflects":[50],"how":[51,87],"DNN\u2019s":[53,82],"varies":[56],"along":[57],"directions":[62],"considered;":[63],"(c)":[64],"consistent":[67],"with":[68,138],"traditional":[70],"versus":[73],"view":[76],"commonly":[77],"used":[78],"monitor":[80],"progress.":[84],"show":[86],"these":[88],"three":[89,99],"levels":[90],"detail":[92],"can":[93],"be":[94],"easily":[95],"realized":[96],"as":[97],"stages":[100],"Shneiderman\u2019s":[102],"Visual":[103],"Information":[104],"Seeking":[105],"Mantra.":[106],"This":[107],"suggests":[108],"design":[110],"development":[112],"new":[115],"interactive":[116,134],"visualization":[117],"tool":[118],"DNN":[123,151],"learning":[124],"processes.":[125],"example":[129],"showcases":[131],"conceivable":[133],"workflow":[135],"when":[136],"working":[137],"such":[139],"tool.":[141],"Moreover,":[142],"we":[143],"give":[144],"first":[146],"impression":[147],"possible":[150],"hyperparameter":[152],"analysis.":[153]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}