{"id":"https://openalex.org/W2109857912","doi":"https://doi.org/10.1145/1553374.1553526","title":"Robust feature extraction via information theoretic learning","display_name":"Robust feature extraction via information theoretic learning","publication_year":2009,"publication_date":"2009-06-14","ids":{"openalex":"https://openalex.org/W2109857912","doi":"https://doi.org/10.1145/1553374.1553526","mag":"2109857912"},"language":"en","primary_location":{"id":"doi:10.1145/1553374.1553526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","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/A5100776794","display_name":"Xiao\u2013Tong Yuan","orcid":"https://orcid.org/0000-0002-7151-8806"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao-Tong Yuan","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019329695","display_name":"Bao-Gang Hu","orcid":"https://orcid.org/0000-0002-6916-5394"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bao-Gang Hu","raw_affiliation_strings":["Chinese Academy of Sciences, Beijing, China","Chinese Academy of Sciences , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"Chinese Academy of Sciences , Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100776794"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":7.5452,"has_fulltext":false,"cited_by_count":147,"citation_normalized_percentile":{"value":0.9765234,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1193","last_page":"1200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.996999979019165,"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":0.996999979019165,"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":0.9965000152587891,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7880849838256836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6526883840560913},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5775312185287476},{"id":"https://openalex.org/keywords/quadratic-equation","display_name":"Quadratic equation","score":0.5159779191017151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48828125},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4388561248779297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4321511387825012},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41287457942962646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4007892310619354},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3304935693740845},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3206943869590759},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2769513726234436}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7880849838256836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6526883840560913},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5775312185287476},{"id":"https://openalex.org/C129844170","wikidata":"https://www.wikidata.org/wiki/Q41299","display_name":"Quadratic equation","level":2,"score":0.5159779191017151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48828125},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4388561248779297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4321511387825012},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41287457942962646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4007892310619354},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3304935693740845},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3206943869590759},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2769513726234436},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1553374.1553526","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.149.4657","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.4657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.mcgill.ca/~icml2009/papers/21.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.518.1872","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.518.1872","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cbsr.ia.ac.cn/users/xtyuan/Papers/Conference/ICML2009/REDA_icml09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5254479036","display_name":null,"funder_award_id":"60275025","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7552007110","display_name":null,"funder_award_id":"2007DFC10740","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320308380","display_name":"Yale University","ror":"https://ror.org/03v76x132"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"},{"id":"https://openalex.org/F4320323251","display_name":"Agent\u00fara na Podporu V\u00fdskumu a V\u00fdvoja","ror":"https://ror.org/037nx0e70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1480487340","https://openalex.org/W1616726216","https://openalex.org/W1624804034","https://openalex.org/W1770825568","https://openalex.org/W1997567675","https://openalex.org/W2046649434","https://openalex.org/W2064534526","https://openalex.org/W2099918640","https://openalex.org/W2100221277","https://openalex.org/W2104290444","https://openalex.org/W2106253207","https://openalex.org/W2116141292","https://openalex.org/W2116801843","https://openalex.org/W2135160607","https://openalex.org/W2135346934","https://openalex.org/W2136040699","https://openalex.org/W2140151376","https://openalex.org/W2148694408","https://openalex.org/W2154872931","https://openalex.org/W2164678670","https://openalex.org/W2489822048","https://openalex.org/W2997701990","https://openalex.org/W3016094606","https://openalex.org/W3148981562","https://openalex.org/W4249667877","https://openalex.org/W4292023222","https://openalex.org/W6636353856","https://openalex.org/W6682644385","https://openalex.org/W6781870204"],"related_works":["https://openalex.org/W4287880334","https://openalex.org/W4366700029","https://openalex.org/W4285230481","https://openalex.org/W4385769873","https://openalex.org/W4281634296","https://openalex.org/W4319161863","https://openalex.org/W2371687270","https://openalex.org/W4311888330","https://openalex.org/W2517641583","https://openalex.org/W1996690921"],"abstract_inverted_index":{"In":[0,66],"this":[1,87,111],"paper,":[2],"we":[3],"present":[4],"a":[5],"robust":[6],"feature":[7,76],"extraction":[8,77],"framework":[9],"based":[10],"on":[11,92],"information-theoretic":[12],"learning.":[13],"Its":[14],"formulated":[15],"objective":[16,40],"aims":[17],"at":[18],"simultaneously":[19],"maximizing":[20],"the":[21,29,43,68,83,104],"Renyi's":[22,30],"quadratic":[23],"information":[24,32],"potential":[25,33],"of":[26],"features":[27,35,99],"and":[28,36,51,54,73],"cross":[31],"between":[34],"class":[37],"labels.":[38],"This":[39],"function":[41],"reaps":[42],"advantages":[44],"in":[45,62,107],"robustness":[46,109],"from":[47,110],"both":[48],"redescending":[49],"M-estimator":[50],"manifold":[52],"regularization,":[53],"can":[55],"be":[56,82],"efficiently":[57],"optimized":[58],"via":[59],"half-quadratic":[60],"optimization":[61],"an":[63],"iterative":[64],"manner.":[65],"addition,":[67],"popular":[69],"algorithms":[70],"LPP,":[71],"SRDA":[72],"LapRLS":[74],"for":[75],"are":[78],"all":[79],"justified":[80],"to":[81],"special":[84],"cases":[85],"within":[86],"framework.":[88,113],"Extensive":[89],"comparison":[90],"experiments":[91],"several":[93],"real-world":[94],"data":[95],"sets,":[96],"with":[97],"contaminated":[98],"or":[100],"labels,":[101],"well":[102],"validate":[103],"encouraging":[105],"gain":[106],"algorithmic":[108],"proposed":[112]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":19},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":9}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}