{"id":"https://openalex.org/W2969740939","doi":"https://doi.org/10.1109/icip.2019.8802985","title":"Block Randomized Optimization for Adaptive Hypergraph Learning","display_name":"Block Randomized Optimization for Adaptive Hypergraph Learning","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2969740939","doi":"https://doi.org/10.1109/icip.2019.8802985","mag":"2969740939"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8802985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8802985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.08281","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021144162","display_name":"Georgios Karantaidis","orcid":"https://orcid.org/0000-0002-7980-7805"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"George Karantaidis","raw_affiliation_strings":["Aristotle University of Thessaloniki, Thessaloniki, Greece","Aristotle University of\u2029 Thessaloniki"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Aristotle University of\u2029 Thessaloniki","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005706607","display_name":"Ioannis Sarridis","orcid":null},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Sarridis","raw_affiliation_strings":["Aristotle University of Thessaloniki, Thessaloniki, Greece","Aristotle University of\u2029 Thessaloniki"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Aristotle University of\u2029 Thessaloniki","institution_ids":["https://openalex.org/I21370196"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065184406","display_name":"Constantine Kotropoulos","orcid":"https://orcid.org/0000-0001-9939-7930"},"institutions":[{"id":"https://openalex.org/I21370196","display_name":"Aristotle University of Thessaloniki","ror":"https://ror.org/02j61yw88","country_code":"GR","type":"education","lineage":["https://openalex.org/I21370196"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Constantine Kotropoulos","raw_affiliation_strings":["Aristotle University of Thessaloniki, Thessaloniki, Greece","Aristotle University of\u2029 Thessaloniki"],"affiliations":[{"raw_affiliation_string":"Aristotle University of Thessaloniki, Thessaloniki, Greece","institution_ids":["https://openalex.org/I21370196"]},{"raw_affiliation_string":"Aristotle University of\u2029 Thessaloniki","institution_ids":["https://openalex.org/I21370196"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021144162"],"corresponding_institution_ids":["https://openalex.org/I21370196"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09754543,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"62","issue":null,"first_page":"864","last_page":"868"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"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/T10057","display_name":"Face and Expression Recognition","score":0.9979000091552734,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.993399977684021,"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/hypergraph","display_name":"Hypergraph","score":0.7868551015853882},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.7047843337059021},{"id":"https://openalex.org/keywords/block-matrix","display_name":"Block matrix","score":0.5302918553352356},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5139519572257996},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.480984091758728},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.46952739357948303},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4613926410675049},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4597594439983368},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4551146626472473},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4312973916530609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37184804677963257},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3274992108345032},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3235691785812378},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.2809096872806549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20402094721794128},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1947585940361023}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7868551015853882},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.7047843337059021},{"id":"https://openalex.org/C85817219","wikidata":"https://www.wikidata.org/wiki/Q884772","display_name":"Block matrix","level":3,"score":0.5302918553352356},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5139519572257996},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.480984091758728},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.46952739357948303},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4613926410675049},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4597594439983368},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4551146626472473},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4312973916530609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37184804677963257},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3274992108345032},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3235691785812378},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.2809096872806549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20402094721794128},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1947585940361023},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2019.8802985","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8802985","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1908.08281","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.08281","pdf_url":"https://arxiv.org/pdf/1908.08281","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2969740939","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1908.08281v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1908.08281","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1908.08281","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.08281","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.08281","pdf_url":"https://arxiv.org/pdf/1908.08281","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6200000047683716}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2969740939.pdf","grobid_xml":"https://content.openalex.org/works/W2969740939.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W34734421","https://openalex.org/W1534892887","https://openalex.org/W1575701986","https://openalex.org/W1968691112","https://openalex.org/W2005676288","https://openalex.org/W2014854862","https://openalex.org/W2018419001","https://openalex.org/W2057261601","https://openalex.org/W2112008792","https://openalex.org/W2117756735","https://openalex.org/W2119591417","https://openalex.org/W2125197607","https://openalex.org/W2154455818","https://openalex.org/W2170057991","https://openalex.org/W2405397566","https://openalex.org/W2735462031","https://openalex.org/W2768623021","https://openalex.org/W2894882275","https://openalex.org/W2962944036","https://openalex.org/W3115678142","https://openalex.org/W6682494755","https://openalex.org/W6685083254","https://openalex.org/W6755829361"],"related_works":["https://openalex.org/W2971333858","https://openalex.org/W1994761691","https://openalex.org/W2178047982","https://openalex.org/W2972410720","https://openalex.org/W2290340024","https://openalex.org/W2767287503","https://openalex.org/W3093733273","https://openalex.org/W3069326598","https://openalex.org/W1991522926","https://openalex.org/W2095603784","https://openalex.org/W2320933085","https://openalex.org/W2969868193","https://openalex.org/W2937824096","https://openalex.org/W2906571504","https://openalex.org/W3026594100","https://openalex.org/W3113671571","https://openalex.org/W1992603145","https://openalex.org/W2792966702","https://openalex.org/W2963165461","https://openalex.org/W3016426920"],"abstract_inverted_index":{"The":[0],"high-order":[1],"relations":[2],"between":[3],"the":[4,22,77,97,101,109,130],"content":[5],"in":[6,36,100,119],"social":[7],"media":[8],"sharing":[9],"platforms":[10],"are":[11,31],"frequently":[12],"modeled":[13],"by":[14,80,107,123],"a":[15,26,69,90],"hypergraph.":[16],"Either":[17],"hypergraph":[18,62,105,135],"Laplacian":[19],"matrix":[20,24,84],"or":[21],"adjacency":[23],"is":[25,58,93],"big":[27,45],"matrix.":[28],"Randomized":[29],"algorithms":[30],"used":[32],"for":[33,65,95],"low-rank":[34,74],"factorizations":[35],"order":[37],"to":[38,128],"approximately":[39],"decompose":[40],"and":[41,126],"eventually":[42],"invert":[43],"such":[44],"matrices":[46],"fast.":[47],"Here,":[48],"block":[49],"randomized":[50,87],"Singular":[51],"Value":[52],"Decomposition":[53],"(SVD)":[54],"via":[55,86],"subspace":[56],"iteration":[57],"integrated":[59],"within":[60],"adaptive":[61,134],"weight":[63,136],"estimation":[64],"image":[66,120],"tagging,":[67],"as":[68],"first":[70],"approach.":[71],"Specifically,":[72],"creating":[73],"submatrices":[75],"along":[76],"main":[78],"diagonal":[79],"tessellation":[81],"permits":[82],"fast":[83],"inversions":[85],"SVD.":[88],"Moreover,":[89],"second":[91],"approach":[92],"proposed":[94,114],"solving":[96],"linear":[98],"system":[99],"optimization":[102],"problem":[103],"of":[104,133],"learning":[106],"employing":[108],"conjugate":[110],"gradient":[111],"method.":[112],"Both":[113],"approaches":[115],"achieve":[116],"high":[117],"accuracy":[118],"tagging":[121],"measured":[122],"F1":[124],"score":[125],"succeed":[127],"reduce":[129],"computational":[131],"requirements":[132],"estimation.":[137]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}