{"id":"https://openalex.org/W3207492555","doi":"https://doi.org/10.3390/e23101360","title":"Information Bottleneck Theory Based Exploration of Cascade Learning","display_name":"Information Bottleneck Theory Based Exploration of Cascade Learning","publication_year":2021,"publication_date":"2021-10-18","ids":{"openalex":"https://openalex.org/W3207492555","doi":"https://doi.org/10.3390/e23101360","mag":"3207492555","pmid":"https://pubmed.ncbi.nlm.nih.gov/34682084"},"language":"en","primary_location":{"id":"doi:10.3390/e23101360","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101360","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1360/pdf?version=1634800789","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/10/1360/pdf?version=1634800789","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103049805","display_name":"Xin Du","orcid":"https://orcid.org/0000-0002-7948-4081"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xin Du","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK"],"raw_orcid":"https://orcid.org/0000-0002-7948-4081","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077531047","display_name":"Katayoun Farrahi","orcid":"https://orcid.org/0000-0001-6775-127X"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Katayoun Farrahi","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK"],"raw_orcid":"https://orcid.org/0000-0001-6775-127X","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK","institution_ids":["https://openalex.org/I43439940"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033579333","display_name":"Mahesan Niranjan","orcid":"https://orcid.org/0000-0001-7021-140X"},"institutions":[{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mahesan Niranjan","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK"],"raw_orcid":"https://orcid.org/0000-0001-7021-140X","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton SO17 3AS, UK","institution_ids":["https://openalex.org/I43439940"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103049805"],"corresponding_institution_ids":["https://openalex.org/I43439940"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.1399,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.57143656,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"23","issue":"10","first_page":"1360","last_page":"1360"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9876000285148621,"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/T10320","display_name":"Neural Networks and Applications","score":0.9876000285148621,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9865000247955322,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9855999946594238,"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/cascade","display_name":"Cascade","score":0.8167710304260254},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7603100538253784},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5560083389282227},{"id":"https://openalex.org/keywords/information-cascade","display_name":"Information cascade","score":0.5292348861694336},{"id":"https://openalex.org/keywords/information-bottleneck-method","display_name":"Information bottleneck method","score":0.4800640046596527},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.42459791898727417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36723172664642334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3467581868171692},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23454701900482178},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.18080666661262512},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1669151484966278},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1170298159122467}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.8167710304260254},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7603100538253784},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5560083389282227},{"id":"https://openalex.org/C27286358","wikidata":"https://www.wikidata.org/wiki/Q6031027","display_name":"Information cascade","level":2,"score":0.5292348861694336},{"id":"https://openalex.org/C60008888","wikidata":"https://www.wikidata.org/wiki/Q6031013","display_name":"Information bottleneck method","level":3,"score":0.4800640046596527},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.42459791898727417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36723172664642334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3467581868171692},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23454701900482178},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.18080666661262512},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1669151484966278},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1170298159122467},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e23101360","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101360","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1360/pdf?version=1634800789","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34682084","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34682084","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:eprints.soton.ac.uk:452209","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:34ca683b9d5d476f9052ca29c4fe6fac","is_oa":true,"landing_page_url":"https://doaj.org/article/34ca683b9d5d476f9052ca29c4fe6fac","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 23, Iss 10, p 1360 (2021)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8535168","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8535168","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23101360","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23101360","pdf_url":"https://www.mdpi.com/1099-4300/23/10/1360/pdf?version=1634800789","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G11400541","display_name":"Artificial and Augmented Intelligence for Automated Scientific Discovery","funder_award_id":"EP/S000356/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G3069159407","display_name":null,"funder_award_id":"EP/S000356/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3207492555.pdf","grobid_xml":"https://content.openalex.org/works/W3207492555.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W134960717","https://openalex.org/W1966347487","https://openalex.org/W1988605894","https://openalex.org/W1990308864","https://openalex.org/W1995875735","https://openalex.org/W2095350947","https://openalex.org/W2108598243","https://openalex.org/W2110798204","https://openalex.org/W2114011790","https://openalex.org/W2117539524","https://openalex.org/W2123504579","https://openalex.org/W2129905273","https://openalex.org/W2149197198","https://openalex.org/W2483908706","https://openalex.org/W2566079294","https://openalex.org/W2622719862","https://openalex.org/W2767204723","https://openalex.org/W2772323041","https://openalex.org/W2788295695","https://openalex.org/W2880214242","https://openalex.org/W2902907165","https://openalex.org/W2906889882","https://openalex.org/W2907407288","https://openalex.org/W2911560375","https://openalex.org/W2914300050","https://openalex.org/W2943160321","https://openalex.org/W2962779416","https://openalex.org/W2971729523","https://openalex.org/W2982864623","https://openalex.org/W2993510279","https://openalex.org/W2998249317","https://openalex.org/W3038705269","https://openalex.org/W3103428075","https://openalex.org/W3106022083","https://openalex.org/W3111316593","https://openalex.org/W3118608800","https://openalex.org/W3125127048","https://openalex.org/W3173703884","https://openalex.org/W3175240777","https://openalex.org/W6637108112","https://openalex.org/W6676553272","https://openalex.org/W6748205129","https://openalex.org/W6752051073","https://openalex.org/W6774719616","https://openalex.org/W6775239935"],"related_works":["https://openalex.org/W4401325445","https://openalex.org/W2622284819","https://openalex.org/W1504394672","https://openalex.org/W3089381707","https://openalex.org/W2038891404","https://openalex.org/W3104987177","https://openalex.org/W4285254085","https://openalex.org/W2810784123","https://openalex.org/W3034190530","https://openalex.org/W3041929574"],"abstract_inverted_index":{"In":[0,67],"solving":[1],"challenging":[2],"pattern":[3],"recognition":[4],"problems,":[5],"deep":[6,86],"neural":[7,87,161],"networks":[8,88],"have":[9],"shown":[10,95],"excellent":[11],"performance":[12,107],"by":[13,138],"forming":[14],"powerful":[15],"mappings":[16],"between":[17],"inputs":[18],"and":[19,24,60,101,128,145],"targets,":[20,127],"learning":[21,45],"representations":[22,35],"(features)":[23],"making":[25],"subsequent":[26],"predictions.":[27],"A":[28],"recent":[29],"tool":[30],"to":[31,56,63,76,84,111],"help":[32],"understand":[33,77],"how":[34,78],"are":[36],"formed":[37],"is":[38,108],"based":[39],"on":[40,46,117],"observing":[41],"the":[42,54,57,61,64,157],"dynamics":[43],"of":[44,159,167],"an":[47,72,140],"information":[48,73,125,141],"plane":[49],"using":[50],"mutual":[51],"information,":[52],"linking":[53],"input":[55],"representation":[58,62],"(I(X;T))":[59],"target":[65],"(I(T;Y)).":[66],"this":[68,136],"paper,":[69],"we":[70],"use":[71],"theoretical":[74],"approach":[75],"Cascade":[79],"Learning":[80],"(CL),":[81],"a":[82,152,160],"method":[83],"train":[85],"layer-by-layer,":[89],"learns":[90],"representations,":[91],"as":[92,151],"CL":[93,122],"has":[94],"comparable":[96],"results":[97],"while":[98],"saving":[99],"computation":[100],"memory":[102],"costs.":[103],"We":[104,134],"observe":[105],"that":[106,147,163],"not":[109],"linked":[110],"information-compression,":[112],"which":[113],"differs":[114],"from":[115],"observation":[116],"End-to-End":[118],"(E2E)":[119],"learning.":[120],"Additionally,":[121],"can":[123,149],"inherit":[124],"about":[126],"gradually":[129],"specialise":[130],"extracted":[131],"features":[132],"layer-by-layer.":[133],"evaluate":[135],"effect":[137],"proposing":[139],"transition":[142],"ratio,":[143],"I(T;Y)/I(X;T),":[144],"show":[146],"it":[148],"serve":[150],"useful":[153],"heuristic":[154],"in":[155],"setting":[156],"depth":[158],"network":[162],"achieves":[164],"satisfactory":[165],"accuracy":[166],"classification.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}