{"id":"https://openalex.org/W7154629129","doi":"https://doi.org/10.48550/arxiv.2604.13179","title":"HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization","display_name":"HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization","publication_year":2026,"publication_date":"2026-04-14","ids":{"openalex":"https://openalex.org/W7154629129","doi":"https://doi.org/10.48550/arxiv.2604.13179"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.13179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.13179","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133771590","display_name":"Trinh Tran","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tran, Trinh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126111881","display_name":"Binh Nguyen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen, Binh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5021671983","display_name":"Truong X. Nghiem","orcid":"https://orcid.org/0000-0003-4841-3800"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nghiem, Truong X.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.6075999736785889,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.6075999736785889,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.0885000005364418,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.032999999821186066,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.6625000238418579},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.6492000222206116},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5263000130653381},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.5231999754905701},{"id":"https://openalex.org/keywords/constrained-optimization","display_name":"Constrained optimization","score":0.4957999885082245},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.47360000014305115},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.4542999863624573},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.4268999993801117}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6625000238418579},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.6492000222206116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6402999758720398},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6122000217437744},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5263000130653381},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.5231999754905701},{"id":"https://openalex.org/C55660270","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization","level":2,"score":0.4957999885082245},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.47360000014305115},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.4268999993801117},{"id":"https://openalex.org/C2989514635","wikidata":"https://www.wikidata.org/wiki/Q5164377","display_name":"Constrained optimization problem","level":3,"score":0.382099986076355},{"id":"https://openalex.org/C50862404","wikidata":"https://www.wikidata.org/wiki/Q3075259","display_name":"Proper convex function","level":5,"score":0.3409999907016754},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.33640000224113464},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3165000081062317},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.29899999499320984},{"id":"https://openalex.org/C12108790","wikidata":"https://www.wikidata.org/wiki/Q2234833","display_name":"Convex analysis","level":4,"score":0.29750001430511475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.275299996137619},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.13179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.13179","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13179","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"HUANet,":[3],"a":[4,23,64,81],"constrained":[5,29,123],"deep":[6],"neural":[7,25,66],"network":[8,26,67,87],"architecture":[9,121],"that":[10],"unrolls":[11],"the":[12,15,73,86,102,105,116,119],"iterations":[13],"of":[14,19,104,118],"Alternating":[16],"Direction":[17],"Method":[18],"Multipliers":[20],"(ADMM)":[21],"into":[22],"trainable":[24],"for":[27,122],"solving":[28],"convex":[30],"optimization":[31,124],"problems.":[32,125],"Existing":[33],"end-to-end":[34],"learning":[35],"methods":[36],"operate":[37],"as":[38,95],"black-box":[39],"mappings":[40],"from":[41],"parameters":[42],"to":[43,52,71,100,114],"solutions,":[44],"often":[45],"lacking":[46],"explicit":[47],"optimality":[48,93],"principles":[49],"and":[50,62],"failing":[51],"enforce":[53],"constraints.":[54],"To":[55],"address":[56],"this":[57],"limitation,":[58],"we":[59,90],"unroll":[60],"ADMM":[61],"embed":[63],"hard-constrained":[65],"at":[68,85],"each":[69],"iteration":[70],"accelerate":[72],"algorithm,":[74],"where":[75],"equality":[76],"constraints":[77,97],"are":[78,112],"enforced":[79],"via":[80],"differentiable":[82],"correction":[83],"stage":[84],"output.":[88],"Furthermore,":[89],"incorporate":[91],"first-order":[92],"conditions":[94],"soft":[96],"during":[98],"training":[99],"promote":[101],"convergence":[103],"proposed":[106,120],"unrolled":[107],"algorithm.":[108],"Extensive":[109],"numerical":[110],"experiments":[111],"conducted":[113],"validate":[115],"effectiveness":[117]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-17T00:00:00"}
