{"id":"https://openalex.org/W4289655361","doi":"https://doi.org/10.1109/isit50566.2022.9834845","title":"Neural Estimation of the Rate-Distortion Function for Massive Datasets","display_name":"Neural Estimation of the Rate-Distortion Function for Massive Datasets","publication_year":2022,"publication_date":"2022-06-26","ids":{"openalex":"https://openalex.org/W4289655361","doi":"https://doi.org/10.1109/isit50566.2022.9834845"},"language":"en","primary_location":{"id":"doi:10.1109/isit50566.2022.9834845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834845","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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 International Symposium on Information Theory (ISIT)","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/A5080594124","display_name":"Eric Lei","orcid":"https://orcid.org/0000-0001-8788-4117"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Eric Lei","raw_affiliation_strings":["University of Pennsylvania,Department of Electrical and Systems Engineering","Department of Electrical and Systems Engineering, University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,Department of Electrical and Systems Engineering","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059354479","display_name":"Hamed Hassani","orcid":"https://orcid.org/0000-0002-9448-8750"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamed Hassani","raw_affiliation_strings":["University of Pennsylvania,Department of Electrical and Systems Engineering","Department of Electrical and Systems Engineering, University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,Department of Electrical and Systems Engineering","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080725457","display_name":"Shirin Saeedi Bidokhti","orcid":"https://orcid.org/0000-0002-3790-202X"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shirin Saeedi Bidokhti","raw_affiliation_strings":["University of Pennsylvania,Department of Electrical and Systems Engineering","Department of Electrical and Systems Engineering, University of Pennsylvania"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,Department of Electrical and Systems Engineering","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080594124"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":0.2399,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57200913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"608","last_page":"613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9990000128746033,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9986000061035156,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9983999729156494,"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/lossy-compression","display_name":"Lossy compression","score":0.8857187032699585},{"id":"https://openalex.org/keywords/rate-distortion","display_name":"Rate distortion","score":0.7191207408905029},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.7127549648284912},{"id":"https://openalex.org/keywords/distortion-function","display_name":"Distortion function","score":0.7077226042747498},{"id":"https://openalex.org/keywords/rate\u2013distortion-theory","display_name":"Rate\u2013distortion theory","score":0.7062321901321411},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6750744581222534},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5502689480781555},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5302032232284546},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5027134418487549},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48277249932289124},{"id":"https://openalex.org/keywords/rate\u2013distortion-optimization","display_name":"Rate\u2013distortion optimization","score":0.42497190833091736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39777621626853943},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3301028609275818},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32366085052490234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22168654203414917},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.13999199867248535},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08341348171234131},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.06875461339950562},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.06385022401809692}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.8857187032699585},{"id":"https://openalex.org/C2982755384","wikidata":"https://www.wikidata.org/wiki/Q843483","display_name":"Rate distortion","level":3,"score":0.7191207408905029},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7127549648284912},{"id":"https://openalex.org/C2780803321","wikidata":"https://www.wikidata.org/wiki/Q5283073","display_name":"Distortion function","level":3,"score":0.7077226042747498},{"id":"https://openalex.org/C64185310","wikidata":"https://www.wikidata.org/wiki/Q843483","display_name":"Rate\u2013distortion theory","level":3,"score":0.7062321901321411},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6750744581222534},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5502689480781555},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5302032232284546},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5027134418487549},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48277249932289124},{"id":"https://openalex.org/C50056821","wikidata":"https://www.wikidata.org/wiki/Q774502","display_name":"Rate\u2013distortion optimization","level":5,"score":0.42497190833091736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39777621626853943},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3301028609275818},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32366085052490234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22168654203414917},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.13999199867248535},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08341348171234131},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.06875461339950562},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.06385022401809692},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.0},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit50566.2022.9834845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit50566.2022.9834845","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"2022 IEEE International Symposium on Information Theory (ISIT)","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 International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W135467536","https://openalex.org/W1515040589","https://openalex.org/W1995875735","https://openalex.org/W2029236670","https://openalex.org/W2063299195","https://openalex.org/W2080570118","https://openalex.org/W2143648696","https://openalex.org/W2148986322","https://openalex.org/W2552465432","https://openalex.org/W2739748921","https://openalex.org/W2767580541","https://openalex.org/W2803832867","https://openalex.org/W2919115771","https://openalex.org/W2939596270","https://openalex.org/W2949573729","https://openalex.org/W2962676454","https://openalex.org/W2962921917","https://openalex.org/W2963506485","https://openalex.org/W2963684088","https://openalex.org/W2997095142","https://openalex.org/W3095497211","https://openalex.org/W3161983439","https://openalex.org/W3204342033","https://openalex.org/W3215157502","https://openalex.org/W4206471589","https://openalex.org/W4286908367","https://openalex.org/W4294567867","https://openalex.org/W4320013936","https://openalex.org/W4376479271","https://openalex.org/W6685352114","https://openalex.org/W6734035190","https://openalex.org/W6741832134","https://openalex.org/W6745847804","https://openalex.org/W6749101112","https://openalex.org/W6752051073","https://openalex.org/W6756138707","https://openalex.org/W6761784523","https://openalex.org/W6772058020","https://openalex.org/W6801321508","https://openalex.org/W6802933752","https://openalex.org/W6803548847"],"related_works":["https://openalex.org/W1413489299","https://openalex.org/W3013747218","https://openalex.org/W4289655361","https://openalex.org/W3006218813","https://openalex.org/W2148508315","https://openalex.org/W2343931896","https://openalex.org/W2103981088","https://openalex.org/W2000669813","https://openalex.org/W2059965583","https://openalex.org/W2999286556"],"abstract_inverted_index":{"A":[0],"fundamental":[1],"question":[2],"in":[3,15],"designing":[4],"lossy":[5,28,174],"data":[6,74],"compression":[7,175],"schemes":[8],"is":[9],"how":[10],"well":[11],"one":[12,66],"can":[13,132],"do":[14],"comparison":[16,59],"with":[17,63,177],"the":[18,23,32,50,69,73,77,87,95,104,109,135,142,153,159,180],"rate-distortion":[19,51,105,136,143,154,160],"function,":[20],"which":[21,56],"describes":[22],"known":[24],"theoretical":[25,127],"limits":[26],"of":[27,35,60,72,97,152],"compression.":[29],"Motivated":[30],"by":[31,145],"empirical":[33,70],"success":[34],"deep":[36],"neural":[37,115],"network":[38],"(DNN)":[39],"compressors":[40,62,147],"on":[41,53,121,179],"large,":[42],"real-world":[43],"data,":[44,55],"we":[45,102,139,157],"investigate":[46],"methods":[47],"to":[48,170],"estimate":[49,134],"function":[52],"such":[54,93],"would":[57],"allow":[58],"DNN":[61,146],"optimality.":[64],"While":[65],"could":[67],"use":[68],"distribution":[71],"and":[75,91,107,125,162,166,183],"apply":[76],"Blahut-Arimoto":[78],"algorithm,":[79],"this":[80],"approach":[81],"presents":[82],"several":[83,150],"computational":[84],"challenges":[85],"when":[86],"datasets":[88],"are":[89,148],"large":[90],"high-dimensional,":[92],"as":[94],"case":[96],"modern":[98],"image":[99,123],"datasets.":[100],"Instead,":[101],"reformulate":[103],"objective,":[106],"solve":[108],"resulting":[110],"functional":[111],"optimization":[112],"problem":[113],"using":[114],"networks.":[116],"We":[117],"provide":[118,126],"experimental":[119],"results":[120],"popular":[122],"datasets,":[124],"evidence":[128],"why":[129],"our":[130],"method":[131,169],"accurately":[133],"function.":[137,155],"Additionally,":[138],"show":[140],"that":[141],"achievable":[144,181],"within":[149],"bits":[151],"Lastly,":[156],"connect":[158],"objective":[161],"entropic":[163],"optimal":[164],"transport,":[165],"describe":[167],"a":[168],"implement":[171],"an":[172],"operational":[173],"scheme":[176],"guarantees":[178],"rate":[182],"distortion.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}