{"id":"https://openalex.org/W3013882546","doi":"https://doi.org/10.1109/jsait.2020.2983165","title":"Learning-Based Coded Computation","display_name":"Learning-Based Coded Computation","publication_year":2020,"publication_date":"2020-03-26","ids":{"openalex":"https://openalex.org/W3013882546","doi":"https://doi.org/10.1109/jsait.2020.2983165","mag":"3013882546"},"language":"en","primary_location":{"id":"doi:10.1109/jsait.2020.2983165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsait.2020.2983165","pdf_url":null,"source":{"id":"https://openalex.org/S4210211895","display_name":"IEEE Journal on Selected Areas in Information Theory","issn_l":"2641-8770","issn":["2641-8770"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Information Theory","raw_type":"journal-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/A5034516607","display_name":"Jack Kosaian","orcid":"https://orcid.org/0000-0001-8812-7847"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jack Kosaian","raw_affiliation_strings":["Computer Science Department, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109919225","display_name":"K. V. Rashmi","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"K. V. Rashmi","raw_affiliation_strings":["Computer Science Department, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082710354","display_name":"Shivaram Venkataraman","orcid":"https://orcid.org/0000-0001-9575-7935"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shivaram Venkataraman","raw_affiliation_strings":["Computer Science Department, University of Wisconsin, Madison, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, University of Wisconsin, Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5034516607"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.4662,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.91050538,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"1","issue":"1","first_page":"227","last_page":"236"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9990000128746033,"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":0.9976999759674072,"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/computation","display_name":"Computation","score":0.7810811996459961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7762249708175659},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6196872591972351},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5776373147964478},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5221874117851257},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47439029812812805},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4672636389732361},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4344746470451355},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1745917797088623}],"concepts":[{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.7810811996459961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7762249708175659},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6196872591972351},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5776373147964478},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5221874117851257},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47439029812812805},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4672636389732361},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4344746470451355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1745917797088623},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsait.2020.2983165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsait.2020.2983165","pdf_url":null,"source":{"id":"https://openalex.org/S4210211895","display_name":"IEEE Journal on Selected Areas in Information Theory","issn_l":"2641-8770","issn":["2641-8770"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Information Theory","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G255524836","display_name":null,"funder_award_id":"DGE-1252522","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G298950637","display_name":null,"funder_award_id":"CNS-1838733","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"},{"id":"https://openalex.org/G4863571209","display_name":null,"funder_award_id":"DGE-1745016","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8959063617","display_name":null,"funder_award_id":"CNS-1850483","funder_id":"https://openalex.org/F4320335353","funder_display_name":"National Science Foundation of Sri Lanka"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320310598","display_name":"Amazon Web Services","ror":"https://ror.org/04mv4n011"},{"id":"https://openalex.org/F4320333377","display_name":"Office of the Vice Chancellor for Research and Graduate Education, University of Wisconsin-Madison","ror":null},{"id":"https://openalex.org/F4320335353","display_name":"National Science Foundation of Sri Lanka","ror":"https://ror.org/010xaa060"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1686810756","https://openalex.org/W1982063824","https://openalex.org/W2083613288","https://openalex.org/W2093217068","https://openalex.org/W2112796928","https://openalex.org/W2150620836","https://openalex.org/W2156749117","https://openalex.org/W2194775991","https://openalex.org/W2268466221","https://openalex.org/W2268702383","https://openalex.org/W2553303224","https://openalex.org/W2556205507","https://openalex.org/W2666368276","https://openalex.org/W2741736887","https://openalex.org/W2750384547","https://openalex.org/W2751733006","https://openalex.org/W2787606899","https://openalex.org/W2797583228","https://openalex.org/W2798525132","https://openalex.org/W2806273311","https://openalex.org/W2806909486","https://openalex.org/W2902687529","https://openalex.org/W2941120301","https://openalex.org/W2962850796","https://openalex.org/W2962873681","https://openalex.org/W2963256807","https://openalex.org/W2963374479","https://openalex.org/W2963385530","https://openalex.org/W2963461717","https://openalex.org/W2963706835","https://openalex.org/W2963840672","https://openalex.org/W2963953036","https://openalex.org/W2964088343","https://openalex.org/W2964095159","https://openalex.org/W2964108773","https://openalex.org/W2964121744","https://openalex.org/W2964231443","https://openalex.org/W2964352239","https://openalex.org/W2975971390","https://openalex.org/W2977140747","https://openalex.org/W2981449041","https://openalex.org/W3100515187","https://openalex.org/W3103649678","https://openalex.org/W4285719527","https://openalex.org/W6600609147","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637373629","https://openalex.org/W6682764186","https://openalex.org/W6696085341","https://openalex.org/W6730956707","https://openalex.org/W6738835244","https://openalex.org/W6742061381","https://openalex.org/W6743655711","https://openalex.org/W6747916894","https://openalex.org/W6747961934","https://openalex.org/W6752557422"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2055243143","https://openalex.org/W4231775656","https://openalex.org/W2611989081","https://openalex.org/W2046435967","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W2383646825","https://openalex.org/W4304166257"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"have":[2],"shown":[3],"the":[4,61,80,86,101,178,188],"potential":[5,179],"for":[6,67,136,180,187,193],"coded":[7,24,56,65,81,89,105,123,191],"computation":[8,25,57,66,82,90,106,124,192],"to":[9,30,59,91,94,107,183],"impart":[10],"resilience":[11,93],"against":[12],"slowdowns":[13,168],"and":[14,148,162],"failures":[15],"that":[16,73,121,169],"occur":[17,170],"in":[18,114,166,171],"distributed":[19],"computing":[20],"systems.":[21],"However,":[22],"existing":[23],"approaches":[26,182],"are":[27],"either":[28],"unable":[29],"support":[31,37],"non-linear":[32,42,69,97,195],"computations,":[33],"or":[34],"can":[35,84],"only":[36],"a":[38,54,111,137],"limited":[39],"subset":[40],"of":[41,63,76,88,103,128,139,190],"computations":[43],"while":[44],"requiring":[45],"high":[46],"resource":[47],"overhead.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"propose":[53],"learning-based":[55,104,122,181],"framework":[58,83],"overcome":[60],"challenges":[62],"performing":[64],"general":[68,96],"functions.":[70],"We":[71,99,151],"show":[72,120,163],"careful":[74],"use":[75,189],"machine":[77],"learning":[78],"within":[79],"extend":[85],"reach":[87],"imparting":[92],"more":[95],"computations.":[98,196],"showcase":[100],"applicability":[102],"neural":[108,134,172],"network":[109,173],"inference,":[110],"major":[112],"workload":[113],"production":[115],"services.":[116],"Our":[117],"evaluation":[118],"results":[119,130,176],"enables":[125],"accurate":[126],"reconstruction":[127],"unavailable":[129],"from":[131],"widely":[132],"deployed":[133],"networks":[135],"variety":[138],"inference":[140],"tasks":[141],"such":[142],"as":[143],"image":[144],"classification,":[145],"speech":[146],"recognition,":[147],"object":[149],"localization.":[150],"implement":[152],"our":[153],"proposed":[154],"approach":[155],"atop":[156],"an":[157],"open-source":[158],"prediction":[159],"serving":[160],"system":[161],"its":[164],"promise":[165],"alleviating":[167],"inference.":[174],"These":[175],"indicate":[177],"open":[184],"new":[185],"doors":[186],"broader,":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}
