{"id":"https://openalex.org/W4292794776","doi":"https://doi.org/10.1109/cvprw56347.2022.00316","title":"Conjugate Adder Net (CAddNet) - a Space-Efficient Approximate CNN","display_name":"Conjugate Adder Net (CAddNet) - a Space-Efficient Approximate CNN","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4292794776","doi":"https://doi.org/10.1109/cvprw56347.2022.00316"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw56347.2022.00316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw56347.2022.00316","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5074323583","display_name":"Lulan Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Lulan Shen","raw_affiliation_strings":["McGill University,Montreal,Canada","McGill University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029947593","display_name":"Maryam Ziaeefard","orcid":"https://orcid.org/0000-0003-4490-1268"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Maryam Ziaeefard","raw_affiliation_strings":["McGill University,Montreal,Canada","McGill University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034701871","display_name":"Brett H. Meyer","orcid":"https://orcid.org/0000-0002-6650-3298"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Brett Meyer","raw_affiliation_strings":["McGill University,Montreal,Canada","McGill University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091600002","display_name":"Warren J. Gross","orcid":"https://orcid.org/0000-0002-6226-6037"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Warren Gross","raw_affiliation_strings":["McGill University,Montreal,Canada","McGill University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079264223","display_name":"James J. Clark","orcid":"https://orcid.org/0000-0002-4512-6171"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"James J. Clark","raw_affiliation_strings":["McGill University,Montreal,Canada","McGill University, Montreal, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074323583"],"corresponding_institution_ids":["https://openalex.org/I5023651"],"apc_list":null,"apc_paid":null,"fwci":0.9587,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68540463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"40","issue":null,"first_page":"2792","last_page":"2796"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10363","display_name":"Low-power high-performance VLSI design","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9939000010490417,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adder","display_name":"Adder","score":0.9114993810653687},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.6505407691001892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6177997589111328},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5650177001953125},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.49959516525268555},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.4926019310951233},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4901197850704193},{"id":"https://openalex.org/keywords/conjugate","display_name":"Conjugate","score":0.47821328043937683},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4737311601638794},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.4331987500190735},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3495054244995117},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2803284823894501},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.0753067135810852}],"concepts":[{"id":"https://openalex.org/C164620267","wikidata":"https://www.wikidata.org/wiki/Q376953","display_name":"Adder","level":3,"score":0.9114993810653687},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.6505407691001892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6177997589111328},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5650177001953125},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.49959516525268555},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.4926019310951233},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4901197850704193},{"id":"https://openalex.org/C197336794","wikidata":"https://www.wikidata.org/wiki/Q5161150","display_name":"Conjugate","level":2,"score":0.47821328043937683},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4737311601638794},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.4331987500190735},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3495054244995117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2803284823894501},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0753067135810852},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvprw56347.2022.00316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw56347.2022.00316","pdf_url":null,"source":{"id":"https://openalex.org/S4363607748","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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":17,"referenced_works":["https://openalex.org/W2020217519","https://openalex.org/W2145104756","https://openalex.org/W2468306622","https://openalex.org/W2469490737","https://openalex.org/W2946711010","https://openalex.org/W3034344052","https://openalex.org/W3118608800","https://openalex.org/W3125729979","https://openalex.org/W3168396991","https://openalex.org/W3211884292","https://openalex.org/W4243472810","https://openalex.org/W6719896775","https://openalex.org/W6720242923","https://openalex.org/W6787972765","https://openalex.org/W6789584077","https://openalex.org/W6796458840","https://openalex.org/W6804167860"],"related_works":["https://openalex.org/W3187512444","https://openalex.org/W1531940793","https://openalex.org/W2796629095","https://openalex.org/W2995154758","https://openalex.org/W3142326970","https://openalex.org/W4287904518","https://openalex.org/W2999956363","https://openalex.org/W2108554563","https://openalex.org/W2028996897","https://openalex.org/W1577384672"],"abstract_inverted_index":{"The":[0,110],"AdderNet":[1],"was":[2],"recently":[3],"developed":[4],"as":[5,106,116],"a":[6,92,98],"way":[7],"to":[8,17,53,124],"implement":[9],"deep":[10],"neural":[11],"networks":[12],"without":[13],"needing":[14],"multiplication":[15],"operations":[16],"combine":[18],"weights":[19,29],"and":[20,30,46,80],"inputs.":[21],"Instead,":[22],"absolute":[23,73],"values":[24,74],"of":[25,41,75,78],"the":[26,36,47,61,69,72,81],"difference":[27,70],"between":[28,71],"inputs":[31,79],"are":[32],"used,":[33],"greatly":[34],"reducing":[35],"gate-level":[37],"implementation":[38],"complexity.":[39],"Training":[40],"AdderNets":[42],"is":[43],"challenging,":[44],"however,":[45],"loss":[48],"curves":[49,122],"during":[50],"training":[51,115,121],"tend":[52],"fluctuate":[54],"significantly.":[55],"In":[56],"this":[57,86],"paper":[58],"we":[59],"propose":[60],"Conjugate":[62],"Adder":[63],"Network,":[64],"or":[65],"CAddNet,":[66],"which":[67],"uses":[68],"conjugate":[76],"pairs":[77],"weights.":[82],"We":[83],"show":[84],"that":[85],"can":[87],"be":[88],"implemented":[89],"simply":[90],"via":[91],"single":[93],"minimum":[94],"operation,":[95],"resulting":[96],"in":[97,102],"roughly":[99],"50%":[100],"reduction":[101],"logic":[103],"gate":[104],"complexity":[105],"compared":[107,117],"with":[108,118],"AdderNets.":[109],"CAddNet":[111],"method":[112],"also":[113],"stabilizes":[114],"AdderNets,":[119],"yielding":[120],"similar":[123],"standard":[125],"CNNs.":[126]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2025-10-10T00:00:00"}