{"id":"https://openalex.org/W2563465138","doi":"https://doi.org/10.1109/dicta.2016.7797063","title":"MLE-Based Learning on Grassmann Manifolds","display_name":"MLE-Based Learning on Grassmann Manifolds","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2563465138","doi":"https://doi.org/10.1109/dicta.2016.7797063","mag":"2563465138"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2016.7797063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7797063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103127139","display_name":"Muhammad Ali","orcid":"https://orcid.org/0000-0002-9128-6504"},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Muhammad Ali","raw_affiliation_strings":["School of Computing and Mathematics, Charles Sturt University Bathurst, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Mathematics, Charles Sturt University Bathurst, NSW, Australia","institution_ids":["https://openalex.org/I153230381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015817857","display_name":"Junbin Gao","orcid":"https://orcid.org/0000-0001-9803-0256"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junbin Gao","raw_affiliation_strings":["Discipline of Business Analytic, The University of Sydney Business School, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Discipline of Business Analytic, The University of Sydney Business School, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012997783","display_name":"Michael Antolovich","orcid":"https://orcid.org/0000-0003-2601-8332"},"institutions":[{"id":"https://openalex.org/I153230381","display_name":"Charles Sturt University","ror":"https://ror.org/00wfvh315","country_code":"AU","type":"education","lineage":["https://openalex.org/I153230381"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Michael Antolovich","raw_affiliation_strings":["School of Computing and Mathematics, Charles Sturt University Bathurst, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Mathematics, Charles Sturt University Bathurst, NSW, Australia","institution_ids":["https://openalex.org/I153230381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18493151,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9873999953269958,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.6026077270507812},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5582905411720276},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.47770145535469055},{"id":"https://openalex.org/keywords/density-estimation","display_name":"Density estimation","score":0.4647155702114105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4517946243286133},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4489228427410126},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4412311613559723},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.413188099861145},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.3798520565032959},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36422574520111084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35794156789779663},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19063156843185425}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.6026077270507812},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5582905411720276},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.47770145535469055},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.4647155702114105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4517946243286133},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4489228427410126},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4412311613559723},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.413188099861145},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3798520565032959},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36422574520111084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35794156789779663},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19063156843185425},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/dicta.2016.7797063","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2016.7797063","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/117700","is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/117700","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W8105021","https://openalex.org/W185495346","https://openalex.org/W371215106","https://openalex.org/W1601795611","https://openalex.org/W1688775013","https://openalex.org/W1785227512","https://openalex.org/W1820849028","https://openalex.org/W1821938769","https://openalex.org/W1964491636","https://openalex.org/W1966385142","https://openalex.org/W1974637548","https://openalex.org/W1986827948","https://openalex.org/W1988130573","https://openalex.org/W1989494851","https://openalex.org/W1995963238","https://openalex.org/W2006766164","https://openalex.org/W2006963646","https://openalex.org/W2025064394","https://openalex.org/W2027492035","https://openalex.org/W2036068690","https://openalex.org/W2049361783","https://openalex.org/W2056526820","https://openalex.org/W2078118580","https://openalex.org/W2088449330","https://openalex.org/W2089373496","https://openalex.org/W2102002080","https://openalex.org/W2108036604","https://openalex.org/W2116022929","https://openalex.org/W2130558599","https://openalex.org/W2136111578","https://openalex.org/W2139916508","https://openalex.org/W2142040002","https://openalex.org/W2145001205","https://openalex.org/W2146966357","https://openalex.org/W2147388619","https://openalex.org/W2149466042","https://openalex.org/W2150515037","https://openalex.org/W2151408393","https://openalex.org/W2160204131","https://openalex.org/W2166049352","https://openalex.org/W2167581801","https://openalex.org/W2184356410","https://openalex.org/W2207669591","https://openalex.org/W2218665234","https://openalex.org/W2224882246","https://openalex.org/W2340944510","https://openalex.org/W2398028250","https://openalex.org/W2500307206","https://openalex.org/W3101921002","https://openalex.org/W4205293427","https://openalex.org/W4246202668","https://openalex.org/W4388255116","https://openalex.org/W6607597722","https://openalex.org/W6637359203","https://openalex.org/W6638627579","https://openalex.org/W6675397997","https://openalex.org/W6681637710","https://openalex.org/W6682124274","https://openalex.org/W6686868605","https://openalex.org/W6688298645","https://openalex.org/W6688903232","https://openalex.org/W6712682651"],"related_works":["https://openalex.org/W63219142","https://openalex.org/W1570464650","https://openalex.org/W1528820368","https://openalex.org/W2187148935","https://openalex.org/W1569550976","https://openalex.org/W2543710962","https://openalex.org/W2043285515","https://openalex.org/W1937731701","https://openalex.org/W2061808167","https://openalex.org/W2585385340"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,51],"focus":[4],"on":[5,13,65,75,90],"Maximum":[6,83],"Likelihood":[7,84],"Estimation":[8,85],"(MLE)":[9,86],"technique":[10],"for":[11,26,59],"classification":[12,60,107,125],"Grassmann":[14],"manifolds":[15],"using":[16,112],"matrix":[17],"variate":[18],"Bingham":[19,95],"density":[20,96],"function.":[21],"Unlike":[22],"the":[23,30,76,91,129,134,138],"conventional":[24],"techniques":[25],"multivariate":[27],"distributions":[28],"in":[29],"existing":[31,135],"literature":[32],"e.g.,":[33],"Markov":[34],"chain":[35],"Monte":[36],"Carlo":[37],"(MCMC)":[38],"sampling":[39],"methods,":[40,42,50],"non-parametric":[41],"Expectation":[43],"Maximisation":[44],"(EM)":[45],"iterative":[46],"methods":[47],"or":[48,147],"exact":[49],"demonstrate":[52],"a":[53,105],"new":[54],"way":[55],"of":[56,70,137],"parametric":[57],"modelling":[58],"that":[61,143],"is":[62,73,87,109],"strictly":[63],"based":[64,74,94],"normalising":[66,71],"constant.":[67],"The":[68,82],"evaluation":[69],"constant":[72],"matrix-variate":[77],"Saddle":[78],"Point":[79],"Approximation":[80],"(SPA).":[81],"directly":[88],"employed":[89],"proposed":[92],"manifold":[93],"function":[97],"via":[98],"simple":[99],"Bayesian":[100],"classifier.":[101],"For":[102],"numerical":[103],"experiments":[104],"3-class":[106],"example":[108],"considered":[110],"by":[111],"real":[113],"world":[114],"Caltech":[115],"101":[116],"and":[117,141],"DynTex++":[118],"database.":[119],"We":[120],"have":[121],"compared":[122],"our":[123,144],"average":[124],"accuracy":[126],"rate":[127],"with":[128],"baseline":[130],"results":[131],"taken":[132],"from":[133],"state":[136],"art":[139],"techniques,":[140],"found":[142],"method":[145],"outperforms":[146],"at":[148],"least":[149],"best":[150],"comparable.":[151]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
