{"id":"https://openalex.org/W4385764481","doi":"https://doi.org/10.24963/ijcai.2023/218","title":"Backpropagation of Unrolled Solvers with Folded Optimization","display_name":"Backpropagation of Unrolled Solvers with Folded Optimization","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385764481","doi":"https://doi.org/10.24963/ijcai.2023/218"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/218","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/218","pdf_url":"https://www.ijcai.org/proceedings/2023/0218.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0218.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052480889","display_name":"James Kotary","orcid":"https://orcid.org/0000-0002-4499-8066"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Kotary","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059653202","display_name":"My H. Dinh","orcid":"https://orcid.org/0000-0002-6367-9626"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"My H Dinh","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052534316","display_name":"Ferdinando Fioretto","orcid":"https://orcid.org/0000-0002-1381-6776"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ferdinando Fioretto","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5052534316"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1963","last_page":"1970"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9972000122070312,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9972000122070312,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9955999851226807,"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/T10320","display_name":"Neural Networks and Applications","score":0.9948999881744385,"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/backpropagation","display_name":"Backpropagation","score":0.8477737903594971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8219934105873108},{"id":"https://openalex.org/keywords/solver","display_name":"Solver","score":0.8169538974761963},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.5823342800140381},{"id":"https://openalex.org/keywords/automatic-differentiation","display_name":"Automatic differentiation","score":0.49403196573257446},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4108728766441345},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3687741458415985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.356701135635376},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32674431800842285},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23809245228767395},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08868440985679626},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08041861653327942}],"concepts":[{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.8477737903594971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8219934105873108},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.8169538974761963},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.5823342800140381},{"id":"https://openalex.org/C133512626","wikidata":"https://www.wikidata.org/wiki/Q787371","display_name":"Automatic differentiation","level":3,"score":0.49403196573257446},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4108728766441345},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3687741458415985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.356701135635376},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32674431800842285},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23809245228767395},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08868440985679626},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08041861653327942},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/218","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/218","pdf_url":"https://www.ijcai.org/proceedings/2023/0218.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/218","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2023/218","pdf_url":"https://www.ijcai.org/proceedings/2023/0218.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6190621094","display_name":"Collaborative Research: RI: Small: End-to-end Learning of Fair and Explainable Schedules for Court Systems","funder_award_id":"2232054","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6671297155","display_name":null,"funder_award_id":"CAREER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7538446710","display_name":"CAREER: End-to-end Constrained Optimization Learning","funder_award_id":"2143706","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385764481.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1665115054","https://openalex.org/W1967138577","https://openalex.org/W2106590231","https://openalex.org/W2113642685","https://openalex.org/W2187061624","https://openalex.org/W2505728881","https://openalex.org/W2763081248","https://openalex.org/W2786807178","https://openalex.org/W2891638642","https://openalex.org/W2899771611","https://openalex.org/W2949444583","https://openalex.org/W2950492466","https://openalex.org/W2963123301","https://openalex.org/W2963446712","https://openalex.org/W2971228012","https://openalex.org/W2981603589","https://openalex.org/W2995194170","https://openalex.org/W2998339876","https://openalex.org/W3034232789","https://openalex.org/W3035070476","https://openalex.org/W3097152630","https://openalex.org/W3112828033","https://openalex.org/W3132475526","https://openalex.org/W3133902371","https://openalex.org/W3136027957","https://openalex.org/W3189470799","https://openalex.org/W3214916216","https://openalex.org/W4239957396","https://openalex.org/W4241359251","https://openalex.org/W4242337769","https://openalex.org/W4281750190","https://openalex.org/W4292363360","https://openalex.org/W4301496368","https://openalex.org/W4312790010","https://openalex.org/W4385767982"],"related_works":["https://openalex.org/W4230546540","https://openalex.org/W1543341614","https://openalex.org/W1718642889","https://openalex.org/W2553993726","https://openalex.org/W2039953621","https://openalex.org/W2077306381","https://openalex.org/W4239286941","https://openalex.org/W2088845016","https://openalex.org/W589102260","https://openalex.org/W4225893763"],"abstract_inverted_index":{"The":[0],"integration":[1],"of":[2,32,56,81,104,117,125,142,150],"constrained":[3],"optimization":[4,34,92,131],"models":[5,116],"as":[6],"components":[7],"in":[8,24,71,148],"deep":[9],"networks":[10],"has":[11],"led":[12],"to":[13,108],"promising":[14],"advances":[15],"on":[16,50,90],"many":[17],"specialized":[18],"learning":[19,137],"tasks.":[20],"A":[21],"central":[22],"challenge":[23],"this":[25],"setting":[26],"is":[27,45],"backpropagation":[28],"through":[29,53,130],"the":[30,54,82,91,101,140,143],"solution":[31],"an":[33,57],"problem,":[35],"which":[36,48],"typically":[37],"lacks":[38],"a":[39,109,122],"closed":[40],"form.":[41,94],"One":[42],"typical":[43],"strategy":[44],"algorithm":[46],"unrolling,":[47],"relies":[49],"automatic":[51],"differentiation":[52,80,129],"operations":[55],"iterative":[58],"solver.":[59],"While":[60],"flexible":[61],"and":[62,68,127,147],"general,":[63],"unrolling":[64,126],"can":[65,75],"encounter":[66],"accuracy":[67],"efficiency":[69],"issues":[70,74],"practice.":[72],"These":[73],"be":[76],"avoided":[77],"by":[78],"analytical":[79,115,128],"optimization,":[83,106],"but":[84],"current":[85],"frameworks":[86],"impose":[87],"rigid":[88],"requirements":[89],"problem's":[93],"This":[95],"paper":[96],"provides":[97],"theoretical":[98],"insights":[99],"into":[100],"backward":[102],"pass":[103],"unrolled":[105],"leading":[107],"system":[110],"for":[111],"generating":[112],"efficiently":[113],"solvable":[114],"backpropagation.":[118],"Additionally,":[119],"it":[120],"proposes":[121],"unifying":[123],"view":[124],"mappings.":[132],"Experiments":[133],"over":[134],"various":[135],"model-based":[136],"tasks":[138],"demonstrate":[139],"advantages":[141],"approach":[144],"both":[145],"computationally":[146],"terms":[149],"enhanced":[151],"expressiveness.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
