{"id":"https://openalex.org/W3153114039","doi":"https://doi.org/10.1109/tpami.2021.3073588","title":"Learning Log-Determinant Divergences for Positive Definite Matrices","display_name":"Learning Log-Determinant Divergences for Positive Definite Matrices","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3153114039","doi":"https://doi.org/10.1109/tpami.2021.3073588","mag":"3153114039","pmid":"https://pubmed.ncbi.nlm.nih.gov/33856984"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2021.3073588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3073588","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2104.06461","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024613828","display_name":"Anoop Cherian","orcid":"https://orcid.org/0000-0002-5566-0351"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]},{"id":"https://openalex.org/I4210133125","display_name":"Mitsubishi Electric (Japan)","ror":"https://ror.org/033y26782","country_code":"JP","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125"]}],"countries":["JP","US"],"is_corresponding":true,"raw_author_name":"Anoop Cherian","raw_affiliation_strings":["MERL, Mitsubishi Electric Corp, 13340 Boston, Massachusetts, United States, (e-mail: cherian@merl.com)","Mitsubishi Electric Research Laboratories,#TAB#"],"affiliations":[{"raw_affiliation_string":"MERL, Mitsubishi Electric Corp, 13340 Boston, Massachusetts, United States, (e-mail: cherian@merl.com)","institution_ids":["https://openalex.org/I4210159266"]},{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories,#TAB#","institution_ids":["https://openalex.org/I4210133125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004868519","display_name":"Panagiotis Stanitsas","orcid":null},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]},{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]},{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Panagiotis Stanitsas","raw_affiliation_strings":["CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: stani078@umn.edu)","university of minnesota;"],"affiliations":[{"raw_affiliation_string":"CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: stani078@umn.edu)","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]},{"raw_affiliation_string":"university of minnesota;","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440604","display_name":"Jue Wang","orcid":"https://orcid.org/0000-0002-3641-3136"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jue Wang","raw_affiliation_strings":["Computer Vision Group, Australian National University College of Engineering and Computer Science, 213523 Canberra, Australian Capital Territory, Australia, 0200 (e-mail: jue.wang@anu.edu.au)","AUSTRALIAN NATIONAL UNIVERSITY"],"affiliations":[{"raw_affiliation_string":"Computer Vision Group, Australian National University College of Engineering and Computer Science, 213523 Canberra, Australian Capital Territory, Australia, 0200 (e-mail: jue.wang@anu.edu.au)","institution_ids":["https://openalex.org/I118347636"]},{"raw_affiliation_string":"AUSTRALIAN NATIONAL UNIVERSITY","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021790939","display_name":"Mehrtash Harandi","orcid":"https://orcid.org/0000-0002-6937-6300"},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mehrtash T Harandi","raw_affiliation_strings":["CSE, Monash University, 2541 Clayton, Victoria, Australia, (e-mail: mehrtash.harandi@monash.edu)","Monash#N#        University"],"affiliations":[{"raw_affiliation_string":"CSE, Monash University, 2541 Clayton, Victoria, Australia, (e-mail: mehrtash.harandi@monash.edu)","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Monash#N#        University","institution_ids":["https://openalex.org/I56590836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081890915","display_name":"Vassilios Morellas","orcid":"https://orcid.org/0000-0002-9198-8442"},"institutions":[{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]},{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]},{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vassilios Morellas","raw_affiliation_strings":["CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: morellas@cs.umn.edu)","university of minnesota;"],"affiliations":[{"raw_affiliation_string":"CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: morellas@cs.umn.edu)","institution_ids":["https://openalex.org/I130238516","https://openalex.org/I4210101327"]},{"raw_affiliation_string":"university of minnesota;","institution_ids":["https://openalex.org/I2800403580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109170958","display_name":"Nikolaos Papanikolopoulos","orcid":null},"institutions":[{"id":"https://openalex.org/I2800403580","display_name":"University of Minnesota System","ror":"https://ror.org/03grvy078","country_code":"US","type":"education","lineage":["https://openalex.org/I2800403580"]},{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikos Papanikolopoulos","raw_affiliation_strings":["CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: npapas@cs.umn.edu)","university of minnesota;"],"affiliations":[{"raw_affiliation_string":"CSE, University of Minnesota Twin Cities, 5635 Minneapolis, Minnesota, United States, (e-mail: npapas@cs.umn.edu)","institution_ids":["https://openalex.org/I130238516"]},{"raw_affiliation_string":"university of minnesota;","institution_ids":["https://openalex.org/I2800403580"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5024613828"],"corresponding_institution_ids":["https://openalex.org/I4210133125","https://openalex.org/I4210159266"],"apc_list":null,"apc_paid":null,"fwci":0.1942,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.46681209,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"44","issue":"9","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9994999766349792,"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/T10057","display_name":"Face and Expression Recognition","score":0.9994999766349792,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9976000189781189,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6767475605010986},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.6645409464836121},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6377960443496704},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.587135374546051},{"id":"https://openalex.org/keywords/positive-definite-matrix","display_name":"Positive-definite matrix","score":0.5537744164466858},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5252556204795837},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.5019512176513672},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4940362572669983},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48868992924690247},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4859088957309723},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4799795150756836},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.47159016132354736},{"id":"https://openalex.org/keywords/bregman-divergence","display_name":"Bregman divergence","score":0.4144382178783417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39570507407188416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3915277123451233},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36053720116615295},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2316860556602478},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.22848451137542725},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.20823082327842712},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1455165445804596},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13698628544807434}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6767475605010986},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.6645409464836121},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6377960443496704},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.587135374546051},{"id":"https://openalex.org/C49712288","wikidata":"https://www.wikidata.org/wiki/Q77601250","display_name":"Positive-definite matrix","level":3,"score":0.5537744164466858},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5252556204795837},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.5019512176513672},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4940362572669983},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48868992924690247},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4859088957309723},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4799795150756836},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.47159016132354736},{"id":"https://openalex.org/C149073432","wikidata":"https://www.wikidata.org/wiki/Q4960382","display_name":"Bregman divergence","level":2,"score":0.4144382178783417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39570507407188416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3915277123451233},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36053720116615295},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2316860556602478},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.22848451137542725},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.20823082327842712},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1455165445804596},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13698628544807434},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tpami.2021.3073588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3073588","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:33856984","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33856984","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":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:arXiv.org:2104.06461","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.06461","pdf_url":"https://arxiv.org/pdf/2104.06461","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":null},{"id":"doi:10.48550/arxiv.2104.06461","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2104.06461","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"},{"id":"mag:3153114039","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2104.06461","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2104.06461","pdf_url":"https://arxiv.org/pdf/2104.06461","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":null},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G1123265799","display_name":null,"funder_award_id":"#CNS-1919631","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1464830453","display_name":"The Formation and Climatological Distribution of Tornadoes within Quasi-Linear Convective Systems","funder_award_id":"0100016","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2007549554","display_name":null,"funder_award_id":"#SMA-1028076","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2672126104","display_name":null,"funder_award_id":"#CNS-1514626","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G279641088","display_name":"I/UCRC Phase I: Robots and Sensors for the Human Well-being","funder_award_id":"1439728","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3220612081","display_name":null,"funder_award_id":"#CNS-1338042","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3550481183","display_name":"MRI: Development of an Instrument that Monitors Behaviors Associated with Obsessive-Compulsive Behaviors and Schizophrenia","funder_award_id":"1338042","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4327185696","display_name":null,"funder_award_id":"CE140100016","funder_id":"https://openalex.org/F4320331724","funder_display_name":"Australian Centre for Robotic Vision"},{"id":"https://openalex.org/G4394669038","display_name":"RAPID: Remote Monitoring of Ebola Patients and Their Treating Physicians","funder_award_id":"1514626","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4537483468","display_name":null,"funder_award_id":"CNS-143972","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4783809151","display_name":null,"funder_award_id":"CNS-1514626","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5130680270","display_name":null,"funder_award_id":"R01CA225435","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5394430895","display_name":null,"funder_award_id":"CNS-1919631","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5818015786","display_name":null,"funder_award_id":"CNS-1338042","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6373503634","display_name":null,"funder_award_id":"R01CA225435","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G6538250860","display_name":null,"funder_award_id":"SMA-1028076","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6837500364","display_name":null,"funder_award_id":"#CNS-1439728","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6905660010","display_name":null,"funder_award_id":"CNS-1439728","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7053366139","display_name":null,"funder_award_id":"1028076","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7694202110","display_name":"Phase II IUCRC University of Minnesota: Center for Robots and Sensors for the Human Well-being","funder_award_id":"1939033","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7739308068","display_name":null,"funder_award_id":"#CNS-0934327","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8472640214","display_name":null,"funder_award_id":"#CNS-1039741","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320331724","display_name":"Australian Centre for Robotic Vision","ror":"https://ror.org/02zv9xv82"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3153114039.pdf","grobid_xml":"https://content.openalex.org/works/W3153114039.grobid-xml"},"referenced_works_count":88,"referenced_works":["https://openalex.org/W92310073","https://openalex.org/W566612420","https://openalex.org/W1141113796","https://openalex.org/W1246381107","https://openalex.org/W1483531051","https://openalex.org/W1549083695","https://openalex.org/W1557979711","https://openalex.org/W1568245674","https://openalex.org/W1573082642","https://openalex.org/W1804110266","https://openalex.org/W1961095629","https://openalex.org/W1978100686","https://openalex.org/W1983496390","https://openalex.org/W1985949731","https://openalex.org/W2017441234","https://openalex.org/W2034014085","https://openalex.org/W2039051707","https://openalex.org/W2048192550","https://openalex.org/W2050728566","https://openalex.org/W2053186076","https://openalex.org/W2055070149","https://openalex.org/W2055597244","https://openalex.org/W2062811091","https://openalex.org/W2087844534","https://openalex.org/W2093015317","https://openalex.org/W2096484739","https://openalex.org/W2099095260","https://openalex.org/W2107018568","https://openalex.org/W2116553565","https://openalex.org/W2117890631","https://openalex.org/W2126579184","https://openalex.org/W2133284024","https://openalex.org/W2133323250","https://openalex.org/W2140178321","https://openalex.org/W2142007061","https://openalex.org/W2144093206","https://openalex.org/W2147942061","https://openalex.org/W2150070703","https://openalex.org/W2156222070","https://openalex.org/W2156303437","https://openalex.org/W2156718197","https://openalex.org/W2157444450","https://openalex.org/W2158911079","https://openalex.org/W2159788726","https://openalex.org/W2167164761","https://openalex.org/W2168446235","https://openalex.org/W2169495281","https://openalex.org/W2201853642","https://openalex.org/W2204257188","https://openalex.org/W2321395385","https://openalex.org/W2404400936","https://openalex.org/W2468075526","https://openalex.org/W2517500902","https://openalex.org/W2582016711","https://openalex.org/W2585165747","https://openalex.org/W2593958796","https://openalex.org/W2607948581","https://openalex.org/W2768687865","https://openalex.org/W2776085193","https://openalex.org/W2798909945","https://openalex.org/W2888453526","https://openalex.org/W2962772276","https://openalex.org/W2962905348","https://openalex.org/W2963066927","https://openalex.org/W2963238274","https://openalex.org/W2963550079","https://openalex.org/W2963728031","https://openalex.org/W2963764968","https://openalex.org/W2963959237","https://openalex.org/W2964068697","https://openalex.org/W2964308810","https://openalex.org/W2970723550","https://openalex.org/W3110683067","https://openalex.org/W3139750972","https://openalex.org/W4205293427","https://openalex.org/W4229633200","https://openalex.org/W4312258136","https://openalex.org/W6615889216","https://openalex.org/W6675041395","https://openalex.org/W6677656871","https://openalex.org/W6680810318","https://openalex.org/W6681717327","https://openalex.org/W6682864246","https://openalex.org/W6683161245","https://openalex.org/W6719959352","https://openalex.org/W6730042731","https://openalex.org/W6786768871","https://openalex.org/W6991377603"],"related_works":["https://openalex.org/W3153428249","https://openalex.org/W2742998842","https://openalex.org/W1481694932","https://openalex.org/W1495279923","https://openalex.org/W2892611525","https://openalex.org/W3034838799","https://openalex.org/W2167257437","https://openalex.org/W3104743435","https://openalex.org/W2622869899","https://openalex.org/W2604829508","https://openalex.org/W3035664806","https://openalex.org/W1999984847","https://openalex.org/W1511088115","https://openalex.org/W1489002364","https://openalex.org/W3201579969","https://openalex.org/W2530382149","https://openalex.org/W2275114322","https://openalex.org/W2083397249","https://openalex.org/W1646506067","https://openalex.org/W2398702385"],"abstract_inverted_index":{"Representations":[0],"in":[1,13,58,77,127,163],"the":[2,62,87,146,149,155,189],"form":[3],"of":[4,16,30,64,104,116,148,191],"Symmetric":[5],"Positive":[6],"Definite":[7],"(SPD)":[8],"matrices":[9,41,110],"have":[10],"been":[11],"popularized":[12],"a":[14,51,55,65,78,92,101,128],"variety":[15],"visual":[17,31],"learning":[18,157,170],"applications":[19],"due":[20],"to":[21,25,73,123,140],"their":[22],"demonstrated":[23],"ability":[24],"capture":[26],"rich":[27],"second-order":[28],"statistics":[29],"data.":[32,134],"There":[33],"exist":[34],"several":[35,160],"similarity":[36,75],"measures":[37,76],"for":[38,50,111,182],"comparing":[39],"SPD":[40,109,173],"with":[42,159],"documented":[43],"benefits.":[44],"However,":[45],"selecting":[46],"an":[47],"appropriate":[48],"measure":[49],"given":[52],"problem":[53,158],"remains":[54],"challenge":[56],"and":[57,98,113,130,171,187],"most":[59],"cases,":[60],"is":[61,91,122],"result":[63],"trial-and-error":[66],"process.":[67],"In":[68],"this":[69,82,138],"paper,":[70],"we":[71,84],"propose":[72],"learn":[74,131,141],"data-driven":[79],"manner.":[80],"To":[81],"end,":[83],"capitalize":[85],"on":[86,108,194],"\u03b1\u03b2-log-det":[88],"divergence,":[89],"which":[90],"meta-divergence":[93],"parametrized":[94],"by":[95],"scalars":[96],"\u03b1":[97],"\u03b2,":[99],"subsuming":[100],"wide":[102],"family":[103],"popular":[105],"information":[106],"divergences":[107],"distinct":[112],"discrete":[114],"values":[115],"these":[117,125],"parameters.":[118],"Our":[119],"key":[120],"idea":[121,139],"cast":[124],"parameters":[126],"continuum":[129],"them":[132],"from":[133],"We":[135,153,176],"systematically":[136],"extend":[137],"vector-valued":[142],"parameters,":[143],"thereby":[144],"increasing":[145],"expressiveness":[147],"underlying":[150],"non-linear":[151],"measure.":[152],"conjoin":[154],"divergence":[156],"standard":[161,196],"tasks":[162],"machine":[164],"learning,":[165],"including":[166],"supervised":[167],"discriminative":[168],"dictionary":[169],"unsupervised":[172],"matrix":[174],"clustering.":[175],"present":[177],"Riemannian":[178],"gradient":[179],"descent":[180],"schemes":[181],"optimizing":[183],"our":[184,192],"formulations":[185],"efficiently,":[186],"show":[188],"usefulness":[190],"method":[193],"eight":[195],"computer":[197],"vision":[198],"tasks.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}