{"id":"https://openalex.org/W3211520991","doi":"https://doi.org/10.3233/aic-210127","title":"Pruning by leveraging training dynamics","display_name":"Pruning by leveraging training dynamics","publication_year":2021,"publication_date":"2021-11-05","ids":{"openalex":"https://openalex.org/W3211520991","doi":"https://doi.org/10.3233/aic-210127","mag":"3211520991"},"language":"en","primary_location":{"id":"doi:10.3233/aic-210127","is_oa":false,"landing_page_url":"https://doi.org/10.3233/aic-210127","pdf_url":null,"source":{"id":"https://openalex.org/S176303223","display_name":"AI Communications","issn_l":"0921-7126","issn":["0921-7126","1875-8452"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Communications","raw_type":"journal-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/A5037342172","display_name":"Andrei C. Apostol","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162034","display_name":"Hersenstichting","ror":"https://ror.org/04y8met08","country_code":"NL","type":"nonprofit","lineage":["https://openalex.org/I4210162034"]},{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Andrei C. Apostol","raw_affiliation_strings":["BrainCreators B.V., Amsterdam, The Netherlands","Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BrainCreators B.V., Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I4210162034"]},{"raw_affiliation_string":"Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079566054","display_name":"Maarten Stol","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162034","display_name":"Hersenstichting","ror":"https://ror.org/04y8met08","country_code":"NL","type":"nonprofit","lineage":["https://openalex.org/I4210162034"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Maarten C. Stol","raw_affiliation_strings":["BrainCreators B.V., Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"BrainCreators B.V., Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I4210162034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005753034","display_name":"Patrick Forr\u00e9","orcid":"https://orcid.org/0000-0003-4663-3842"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Patrick Forr\u00e9","raw_affiliation_strings":["Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5037342172"],"corresponding_institution_ids":["https://openalex.org/I4210162034","https://openalex.org/I887064364"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14592638,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"2","first_page":"65","last_page":"85"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9969000220298767,"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/computer-science","display_name":"Computer science","score":0.9203109741210938},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7738550305366516},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.7215265035629272},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5662066340446472},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5194434523582458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4852704703807831},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4427988529205322},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43790143728256226},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21956440806388855},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0658559799194336}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9203109741210938},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7738550305366516},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7215265035629272},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5662066340446472},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5194434523582458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4852704703807831},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4427988529205322},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43790143728256226},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21956440806388855},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0658559799194336},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3233/aic-210127","is_oa":false,"landing_page_url":"https://doi.org/10.3233/aic-210127","pdf_url":null,"source":{"id":"https://openalex.org/S176303223","display_name":"AI Communications","issn_l":"0921-7126","issn":["0921-7126","1875-8452"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Communications","raw_type":"journal-article"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/73d70192-9411-4be9-96b2-95e420938ce1","is_oa":false,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/pruning-by-leveraging-training-dynamics(73d70192-9411-4be9-96b2-95e420938ce1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Apostol, A C, Stol, M C & Forr\u00e9, P 2022, 'Pruning by leveraging training dynamics', AI Communications, vol. 35, no. 2, pp. 65-85. https://doi.org/10.3233/AIC-210127","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:uvapub:oai:dare.uva.nl:publications/73d70192-9411-4be9-96b2-95e420938ce1","is_oa":false,"landing_page_url":"https://dare.uva.nl/personal/pure/en/publications/pruning-by-leveraging-training-dynamics(73d70192-9411-4be9-96b2-95e420938ce1).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"AI Communications, 35(2), 65 - 85. IOS Press","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W196761320","https://openalex.org/W1506342804","https://openalex.org/W1665214252","https://openalex.org/W1959608418","https://openalex.org/W2064675550","https://openalex.org/W2099471712","https://openalex.org/W2114766824","https://openalex.org/W2125389748","https://openalex.org/W2132211083","https://openalex.org/W2167433878","https://openalex.org/W2194775991","https://openalex.org/W2515385951","https://openalex.org/W2768501777","https://openalex.org/W2893749619","https://openalex.org/W2949117887","https://openalex.org/W2952088488","https://openalex.org/W2962835968","https://openalex.org/W2963122961","https://openalex.org/W2963247446","https://openalex.org/W2963363373","https://openalex.org/W2963403868","https://openalex.org/W2963446712","https://openalex.org/W2963674932","https://openalex.org/W2963809228","https://openalex.org/W2963813662","https://openalex.org/W2964121744","https://openalex.org/W2970277060","https://openalex.org/W2970971581","https://openalex.org/W2971275988","https://openalex.org/W2996019573","https://openalex.org/W3007731245","https://openalex.org/W3024929536","https://openalex.org/W3174754110","https://openalex.org/W6989086347"],"related_works":["https://openalex.org/W4295309597","https://openalex.org/W4210794429","https://openalex.org/W4280644903","https://openalex.org/W4280535922","https://openalex.org/W3022098070","https://openalex.org/W4223456145","https://openalex.org/W4309113015","https://openalex.org/W4283697347","https://openalex.org/W4304128395","https://openalex.org/W3199608561"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,16,67],"novel":[3],"pruning":[4,32],"method":[5,29,108],"which":[6],"uses":[7],"the":[8,34,55,61,100],"oscillations":[9],"around":[10],"0,":[11],"i.e.":[12],"sign":[13],"flips,":[14],"that":[15,74,106],"weight":[17],"has":[18,36],"undergone":[19],"during":[20],"training":[21],"in":[22],"order":[23],"to":[24,43],"determine":[25],"its":[26,49],"saliency.":[27],"Our":[28,63],"can":[30,52],"perform":[31],"before":[33],"network":[35],"converged,":[37],"requires":[38],"little":[39],"tuning":[40],"effort":[41],"due":[42],"having":[44],"good":[45],"default":[46],"values":[47],"for":[48,85,94],"hyperparameters,":[50],"and":[51,81,92],"directly":[53],"target":[54],"level":[56],"of":[57,69,87,89,97,99],"sparsity":[58,88],"desired":[59],"by":[60],"user.":[62],"experiments,":[64],"performed":[65],"on":[66],"variety":[68],"object":[70],"classification":[71],"architectures,":[72],"show":[73],"it":[75],"is":[76,109],"competitive":[77],"with":[78,111],"existing":[79],"methods":[80],"achieves":[82],"state-of-the-art":[83],"performance":[84],"levels":[86],"99.6":[90],"%":[91],"above":[93],"2":[95],"out":[96],"3":[98],"architectures":[101],"tested.":[102],"Moreover,":[103],"we":[104,119],"demonstrate":[105],"our":[107,121],"compatible":[110],"quantization,":[112],"another":[113],"model":[114],"compression":[115],"technique.":[116],"For":[117],"reproducibility,":[118],"release":[120],"code":[122],"at":[123],"https://github.com/AndreiXYZ/flipout.":[124]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}