{"id":"https://openalex.org/W2603825910","doi":"https://doi.org/10.1162/neco_a_00958","title":"DC Algorithm for Extended Robust Support Vector Machine","display_name":"DC Algorithm for Extended Robust Support Vector Machine","publication_year":2017,"publication_date":"2017-03-23","ids":{"openalex":"https://openalex.org/W2603825910","doi":"https://doi.org/10.1162/neco_a_00958","mag":"2603825910","pmid":"https://pubmed.ncbi.nlm.nih.gov/28333592"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_00958","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00958","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5044574391","display_name":"Shuhei Fujiwara","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shuhei Fujiwara","raw_affiliation_strings":["TOPGATE Co., Bunkyo-ku, Tokyo, 113-0033, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TOPGATE Co., Bunkyo-ku, Tokyo, 113-0033, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101795095","display_name":"Akiko Takeda","orcid":"https://orcid.org/0000-0002-8846-4496"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Akiko Takeda","raw_affiliation_strings":["Department of Mathematical Analysis and Statistical Inference, Institute of Statistical Mathematics, Tachikawa, Tokyo 190-8562, Japan; and RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Analysis and Statistical Inference, Institute of Statistical Mathematics, Tachikawa, Tokyo 190-8562, Japan; and RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088569462","display_name":"Takafumi Kanamori","orcid":"https://orcid.org/0000-0001-6878-5850"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takafumi Kanamori","raw_affiliation_strings":["Department of Computer Science and Mathematical Informatics, Nagoya University, Chikusa-ku, Nagoya, Aichi 464-8601, Japan; and RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Mathematical Informatics, Nagoya University, Chikusa-ku, Nagoya, Aichi 464-8601, Japan; and RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","institution_ids":["https://openalex.org/I4210126580","https://openalex.org/I60134161"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project, 1-4-1, Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan","institution_ids":["https://openalex.org/I4210126580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5044574391","https://openalex.org/A5088569462","https://openalex.org/A5101795095"],"corresponding_institution_ids":["https://openalex.org/I4210126580","https://openalex.org/I60134161"],"apc_list":null,"apc_paid":null,"fwci":0.4738,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.60328489,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"29","issue":"5","first_page":"1406","last_page":"1438"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991999864578247,"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":0.9991999864578247,"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/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"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/T10545","display_name":"Optimization and Variational Analysis","score":0.9850999712944031,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/support-vector-machine","display_name":"Support vector machine","score":0.8746709227561951},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.7042554616928101},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6321359872817993},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6247463822364807},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6123906970024109},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.5913213491439819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5382497310638428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4831475615501404},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.44102615118026733},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3589168190956116},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33741459250450134},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05995228886604309}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8746709227561951},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7042554616928101},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6321359872817993},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6247463822364807},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6123906970024109},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.5913213491439819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5382497310638428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4831475615501404},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.44102615118026733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3589168190956116},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33741459250450134},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05995228886604309},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/neco_a_00958","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_00958","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718"],"host_organization_lineage_names":["The MIT Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:28333592","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28333592","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":"Neural computation","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7994593859","display_name":"Efficient large-scale robust optimization algorithms and their applications to machine learning","funder_award_id":"15K00031","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8498071073","display_name":"Mathematics and Practical Algorithms for machine Learning methods with non-convex losses","funder_award_id":"16K00044","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W149581298","https://openalex.org/W1512098439","https://openalex.org/W1990494141","https://openalex.org/W1992422840","https://openalex.org/W1997413930","https://openalex.org/W2019291268","https://openalex.org/W2030843733","https://openalex.org/W2036350498","https://openalex.org/W2070579445","https://openalex.org/W2084812512","https://openalex.org/W2089394015","https://openalex.org/W2119821739","https://openalex.org/W2151976295","https://openalex.org/W2153417333","https://openalex.org/W2160353894","https://openalex.org/W2161920802","https://openalex.org/W2162152253","https://openalex.org/W2166765763","https://openalex.org/W2170921838","https://openalex.org/W2215815030","https://openalex.org/W2229839854","https://openalex.org/W2340859457","https://openalex.org/W2499342028","https://openalex.org/W2605467427","https://openalex.org/W3081544918","https://openalex.org/W3120421331","https://openalex.org/W3124407081","https://openalex.org/W4212864101","https://openalex.org/W4239510810","https://openalex.org/W4249667877"],"related_works":["https://openalex.org/W2767160479","https://openalex.org/W112629874","https://openalex.org/W2166551085","https://openalex.org/W1499746122","https://openalex.org/W2913952424","https://openalex.org/W2209805890","https://openalex.org/W1948992892","https://openalex.org/W3168178700","https://openalex.org/W2090763504","https://openalex.org/W1668892176"],"abstract_inverted_index":{"Nonconvex":[0],"variants":[1],"of":[2,38,59,67,77,135,156,176],"support":[3,52],"vector":[4,53],"machines":[5],"(SVMs)":[6],"have":[7],"been":[8],"developed":[9],"for":[10,127],"various":[11],"purposes.":[12],"For":[13],"example,":[14],"robust":[15,51,57,70,148,166],"SVMs":[16,71,167],"attain":[17],"robustness":[18],"to":[19,87],"outliers":[20],"by":[21,41],"using":[22],"a":[23,43,56,123,153],"nonconvex":[24,44,112],"loss":[25],"function,":[26],"while":[27,137],"extended":[28,50,102,116],"[Formula:":[29],"see":[30,33,61,74,145],"text]-SVM":[31,146],"(E[Formula:":[32],"text]-SVM)":[34],"extends":[35],"the":[36,39,78,81,96,101,111,115,164,174,178],"range":[37,103],"hyperparameter":[40,97],"introducing":[42],"constraint.":[45],"Here,":[46],"we":[47,84,121,159],"consider":[48],"an":[49],"machine":[54],"(ER-SVM),":[55],"variant":[58],"E[Formula:":[60,73,144],"text]-SVM.":[62,75],"ER-SVM":[63,162],"combines":[64],"two":[65,79,91,133,179],"types":[66,134],"nonconvexity":[68,136],"from":[69],"and":[72,150],"Because":[76],"nonconvexities,":[80],"existing":[82,165],"algorithm":[83,107,126,130],"proposed":[85],"needs":[86],"be":[88],"divided":[89],"into":[90],"parts":[92],"depending":[93],"on":[94],"whether":[95],"value":[98],"is":[99],"in":[100,114],"or":[104,147],"not.":[105],"The":[106,129],"also":[108],"heuristically":[109],"solves":[110],"problem":[113],"range.":[117],"In":[118],"this":[119],"letter,":[120],"propose":[122],"new,":[124],"efficient":[125],"ER-SVM.":[128,157],"deals":[131],"with":[132],"never":[138],"entailing":[139],"more":[140],"computations":[141],"than":[142],"either":[143],"SVM,":[149],"it":[151],"finds":[152],"critical":[154],"point":[155],"Furthermore,":[158],"show":[160],"that":[161],"includes":[163],"as":[168],"special":[169],"cases.":[170],"Numerical":[171],"experiments":[172],"confirm":[173],"effectiveness":[175],"integrating":[177],"nonconvexities.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
