{"id":"https://openalex.org/W4402426788","doi":"https://doi.org/10.48550/arxiv.2408.06024","title":"Layer-Specific Optimization: Sensitivity Based Convolution Layers Basis Search","display_name":"Layer-Specific Optimization: Sensitivity Based Convolution Layers Basis Search","publication_year":2024,"publication_date":"2024-08-12","ids":{"openalex":"https://openalex.org/W4402426788","doi":"https://doi.org/10.48550/arxiv.2408.06024"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2408.06024","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.06024","pdf_url":"https://arxiv.org/pdf/2408.06024","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2408.06024","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059693936","display_name":"Vasiliy Alekseev","orcid":"https://orcid.org/0000-0001-7930-3650"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Alekseev, Vasiliy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107114019","display_name":"Ilya Lukashevich","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lukashevich, Ilya","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044592516","display_name":"Ilia Zharikov","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zharikov, Ilia","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5011568130","display_name":"Ilya Vasiliev","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vasiliev, Ilya","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059693936"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.4113999903202057,"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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.4113999903202057,"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/sensitivity","display_name":"Sensitivity (control systems)","score":0.7496639490127563},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.6786113381385803},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.607079803943634},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4844496250152588},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.44384101033210754},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4048994183540344},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40421849489212036},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3560757040977478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2371528148651123},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1953481137752533},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1176435649394989},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.11713087558746338},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10237830877304077}],"concepts":[{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.7496639490127563},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.6786113381385803},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.607079803943634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4844496250152588},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.44384101033210754},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4048994183540344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40421849489212036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3560757040977478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2371528148651123},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1953481137752533},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1176435649394989},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.11713087558746338},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10237830877304077},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2408.06024","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.06024","pdf_url":"https://arxiv.org/pdf/2408.06024","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2408.06024","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2408.06024","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2408.06024","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.06024","pdf_url":"https://arxiv.org/pdf/2408.06024","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4402426788.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2378757965","https://openalex.org/W4224903346","https://openalex.org/W2392320810","https://openalex.org/W1593262897","https://openalex.org/W2372869593","https://openalex.org/W2078609410","https://openalex.org/W2384194537","https://openalex.org/W2387724274","https://openalex.org/W2031011156","https://openalex.org/W4382011329"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2,41,195],"models":[3,145],"have":[4],"a":[5,61,82,87,97,187,192],"complex":[6],"architecture":[7],"and":[8,29,132,150,172],"are":[9],"overparameterized.":[10],"The":[11,113],"number":[12,39,74],"of":[13,40,48,66,75,89,100,110,115,128,139,164,175,180,194,201,209],"parameters":[14,42,77],"is":[15,22,78,84,118,183],"more":[16],"than":[17],"the":[18,38,46,49,53,64,67,73,102,108,116,126,134,140,147,151,162,165,170,176,199,207,210],"whole":[19],"dataset,":[20],"which":[21,198],"highly":[23],"resource-consuming.":[24],"This":[25],"complicates":[26],"their":[27],"application":[28],"limits":[30],"its":[31],"usage":[32],"on":[33,144],"different":[34],"devices.":[35],"Reduction":[36],"in":[37,63,197],"helps":[43],"to":[44,60,71,107,119],"reduce":[45,72,161],"size":[47,163],"model,":[50],"but":[51,124,167],"at":[52],"same":[54],"time,":[55],"thoughtlessly":[56],"applied,":[57],"can":[58,158],"lead":[59],"deterioration":[62],"quality":[65,208],"network.":[68,177],"One":[69],"way":[70,99],"model":[76,166],"matrix":[79,83,103,202],"decomposition,":[80],"where":[81],"represented":[85],"as":[86,136],"product":[88],"smaller":[90],"matrices.":[91],"In":[92],"this":[93,181],"paper,":[94],"we":[95,185],"propose":[96,186],"new":[98],"applying":[101],"decomposition":[104,203],"with":[105],"respect":[106],"weights":[109],"convolutional":[111],"layers.":[112],"essence":[114],"method":[117,189],"train":[120],"not":[121,159,205],"all":[122],"convolutions,":[123],"only":[125,160],"subset":[127,193],"convolutions":[129,157],"(basis":[130],"convolutions),":[131],"represent":[133],"rest":[135],"linear":[137],"combinations":[138],"basis":[141,156],"ones.":[142],"Experiments":[143],"from":[146],"ResNet":[148],"family":[149],"CIFAR-10":[152],"dataset":[153],"demonstrate":[154],"that":[155,184],"also":[168],"accelerate":[169],"forward":[171],"backward":[173],"passes":[174],"Another":[178],"contribution":[179],"work":[182],"fast":[188],"for":[190],"selecting":[191],"layers":[196],"use":[200],"does":[204],"degrade":[206],"final":[211],"model.":[212]},"counts_by_year":[],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
