{"id":"https://openalex.org/W4394597776","doi":"https://doi.org/10.1109/wacv57701.2024.00233","title":"Partial Binarization of Neural Networks for Budget-Aware Efficient Learning","display_name":"Partial Binarization of Neural Networks for Budget-Aware Efficient Learning","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4394597776","doi":"https://doi.org/10.1109/wacv57701.2024.00233"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv57701.2024.00233","pdf_url":null,"source":{"id":"https://openalex.org/S4363607979","display_name":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.06739","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051902071","display_name":"Udbhav Bamba","orcid":null},"institutions":[],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Udbhav Bamba","raw_affiliation_strings":["Transmute AI Lab, India"],"affiliations":[{"raw_affiliation_string":"Transmute AI Lab, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078013530","display_name":"Neeraj Anand","orcid":"https://orcid.org/0000-0002-2243-434X"},"institutions":[],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Neeraj Anand","raw_affiliation_strings":["Nyun AI, India"],"affiliations":[{"raw_affiliation_string":"Nyun AI, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014818963","display_name":"Saksham Aggarwal","orcid":null},"institutions":[],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saksham Aggarwal","raw_affiliation_strings":["Transmute AI Lab, India"],"affiliations":[{"raw_affiliation_string":"Transmute AI Lab, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064348917","display_name":"Dilip K. Prasad","orcid":"https://orcid.org/0000-0002-3693-6973"},"institutions":[{"id":"https://openalex.org/I4210095992","display_name":"Centre for Arctic Gas Hydrate, Environment and Climate","ror":"https://ror.org/00p8r6x45","country_code":"NO","type":"facility","lineage":["https://openalex.org/I4210095992","https://openalex.org/I78037679"]},{"id":"https://openalex.org/I78037679","display_name":"UiT The Arctic University of Norway","ror":"https://ror.org/00wge5k78","country_code":"NO","type":"education","lineage":["https://openalex.org/I78037679"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Dilip K. Prasad","raw_affiliation_strings":["UiT The Arctic University of Norway, Norway"],"affiliations":[{"raw_affiliation_string":"UiT The Arctic University of Norway, Norway","institution_ids":["https://openalex.org/I4210095992","https://openalex.org/I78037679"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029422773","display_name":"Deepak Kumar Gupta","orcid":"https://orcid.org/0000-0003-0994-9282"},"institutions":[],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepak K. Gupta","raw_affiliation_strings":["Transmute AI Lab, India"],"affiliations":[{"raw_affiliation_string":"Transmute AI Lab, India","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":{"min":0,"max":84},"biblio":{"volume":null,"issue":null,"first_page":"2325","last_page":"2334"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.7623,"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":0.7623,"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":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8051469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.577072},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.57328975},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41990834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3425982}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv57701.2024.00233","pdf_url":null,"source":{"id":"https://openalex.org/S4363607979","display_name":"2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2211.06739","pdf_url":"https://arxiv.org/pdf/2211.06739","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2211.06739","pdf_url":"https://arxiv.org/pdf/2211.06739","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":34,"referenced_works":["https://openalex.org/W1690739335","https://openalex.org/W1821462560","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2300242332","https://openalex.org/W2319920447","https://openalex.org/W2553303224","https://openalex.org/W2753301142","https://openalex.org/W2805003733","https://openalex.org/W2809624076","https://openalex.org/W2894740066","https://openalex.org/W2896718327","https://openalex.org/W2962851801","https://openalex.org/W2962965870","https://openalex.org/W2963197148","https://openalex.org/W2963363373","https://openalex.org/W2963918968","https://openalex.org/W2970500560","https://openalex.org/W2972343638","https://openalex.org/W2995607862","https://openalex.org/W2997112073","https://openalex.org/W3034297393","https://openalex.org/W3104151879","https://openalex.org/W3104688113","https://openalex.org/W3137147200","https://openalex.org/W3174809603","https://openalex.org/W3183734708","https://openalex.org/W398859631","https://openalex.org/W4212774754","https://openalex.org/W4287824105","https://openalex.org/W4297775537","https://openalex.org/W4297797729","https://openalex.org/W569478347"],"related_works":["https://openalex.org/W4360585206","https://openalex.org/W4321369474","https://openalex.org/W4306674287","https://openalex.org/W4285208911","https://openalex.org/W3215138031","https://openalex.org/W3082895349","https://openalex.org/W3046775127","https://openalex.org/W3009238340","https://openalex.org/W2961085424","https://openalex.org/W2731899572"],"abstract_inverted_index":{"Binarization":[0],"is":[1,46],"a":[2,16,33,43,54,61,151],"powerful":[3],"compression":[4],"technique":[5],"for":[6,82],"neural":[7,64],"networks,":[8],"significantly":[9],"reducing":[10],"FLOPs,":[11],"but":[12,32],"often":[13],"results":[14],"in":[15,19,42,145],"significant":[17],"drop":[18],"model":[20],"performance.":[21],"To":[22],"address":[23],"this":[24,50],"issue,":[25],"partial":[26,58],"binarization":[27],"techniques":[28],"have":[29],"been":[30],"developed,":[31],"systematic":[34],"approach":[35,56],"to":[36,57,91,116,150],"mixing":[37,75],"binary":[38,63,77],"and":[39,78,109,142],"full-precision":[40,79],"parameters":[41],"single":[44],"network":[45,65,90],"still":[47],"lacking.":[48],"In":[49],"paper,":[51],"we":[52,159],"propose":[53],"controlled":[55],"binarization,":[59],"creating":[60],"budgeted":[62],"(B2NN)":[66],"with":[67,148,171],"our":[68],"MixBin":[69,101,165,180],"strategy.":[70],"This":[71],"method":[72],"optimizes":[73],"the":[74,86,89,119,128,136,182],"of":[76,85,88,140],"components,":[80],"allowing":[81],"explicit":[83],"selection":[84,112],"fraction":[87],"remain":[92],"binary.":[93],"Our":[94],"experiments":[95],"show":[96,124],"that":[97,125,161],"B2NNs":[98,126,162],"created":[99],"using":[100],"outperform":[102,127],"those":[103],"from":[104],"random":[105],"or":[106],"iterative":[107],"searches":[108],"state-of-the-art":[110],"layer":[111],"methods":[113],"by":[114,132,164],"up":[115,149],"3%":[117],"on":[118,181],"ImageNet-1K":[120],"dataset.":[121],"We":[122],"also":[123],"structured":[129],"pruning":[130],"baseline":[131],"approximately":[133],"23%":[134],"at":[135],"extreme":[137],"FLOP":[138],"budget":[139],"15%,":[141],"perform":[143],"well":[144],"object":[146],"tracking,":[147],"12.4%":[152],"relative":[153],"improvement":[154],"over":[155,177],"other":[156],"baselines.":[157],"Additionally,":[158],"demonstrate":[160],"developed":[163],"can":[166],"be":[167],"transferred":[168],"across":[169],"datasets,":[170],"some":[172],"cases":[173],"showing":[174],"improved":[175],"performance":[176],"directly":[178],"applying":[179],"downstream":[183],"data.":[184],"1":[187]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4394597776","counts_by_year":[],"updated_date":"2024-12-05T02:10:58.177753","created_date":"2024-04-10"}