{"id":"https://openalex.org/W2744171414","doi":"https://doi.org/10.1162/neco_a_01002","title":"A Robust Regression Framework with Laplace Kernel-Induced Loss","display_name":"A Robust Regression Framework with Laplace Kernel-Induced Loss","publication_year":2017,"publication_date":"2017-08-04","ids":{"openalex":"https://openalex.org/W2744171414","doi":"https://doi.org/10.1162/neco_a_01002","mag":"2744171414","pmid":"https://pubmed.ncbi.nlm.nih.gov/28777723"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_01002","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01002","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/A5032961377","display_name":"Liming Yang","orcid":"https://orcid.org/0000-0003-1475-3073"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liming Yang","raw_affiliation_strings":["College of Science, China Agricultural University, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China Agricultural University, Beijing, 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065085915","display_name":"Zhuo Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuo Ren","raw_affiliation_strings":["College of Science, China Agricultural University, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China Agricultural University, Beijing, 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604313","display_name":"Yidan Wang","orcid":"https://orcid.org/0000-0003-4649-212X"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yidan Wang","raw_affiliation_strings":["College of Science, China Agricultural University, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China Agricultural University, Beijing, 100083, China","institution_ids":["https://openalex.org/I52158045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100708158","display_name":"Hongwei Dong","orcid":"https://orcid.org/0000-0003-2629-2892"},"institutions":[{"id":"https://openalex.org/I52158045","display_name":"China Agricultural University","ror":"https://ror.org/04v3ywz14","country_code":"CN","type":"education","lineage":["https://openalex.org/I52158045"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongwei Dong","raw_affiliation_strings":["College of Science, China Agricultural University, Beijing, 100083, China"],"affiliations":[{"raw_affiliation_string":"College of Science, China Agricultural University, Beijing, 100083, China","institution_ids":["https://openalex.org/I52158045"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032961377","https://openalex.org/A5065085915","https://openalex.org/A5100604313","https://openalex.org/A5100708158"],"corresponding_institution_ids":["https://openalex.org/I52158045"],"apc_list":null,"apc_paid":null,"fwci":2.1788,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.8553052,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"29","issue":"11","first_page":"3014","last_page":"3039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9952999949455261,"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":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5904948711395264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5809054374694824},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.56609046459198},{"id":"https://openalex.org/keywords/laplace-transform","display_name":"Laplace transform","score":0.504892885684967},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5021414756774902},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4970856010913849},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4802734851837158},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.4592130184173584},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45820072293281555},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43094372749328613},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3745388984680176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3442460298538208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2714557349681854},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13171115517616272}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5904948711395264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5809054374694824},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.56609046459198},{"id":"https://openalex.org/C97937538","wikidata":"https://www.wikidata.org/wiki/Q199691","display_name":"Laplace transform","level":2,"score":0.504892885684967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5021414756774902},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4970856010913849},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4802734851837158},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.4592130184173584},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45820072293281555},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43094372749328613},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3745388984680176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3442460298538208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2714557349681854},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13171115517616272},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/neco_a_01002","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01002","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:28777723","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28777723","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":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1491462408","https://openalex.org/W1596717185","https://openalex.org/W1903303072","https://openalex.org/W1973560868","https://openalex.org/W1978996791","https://openalex.org/W2017719067","https://openalex.org/W2025804608","https://openalex.org/W2032938012","https://openalex.org/W2044297353","https://openalex.org/W2050849575","https://openalex.org/W2055718333","https://openalex.org/W2064593130","https://openalex.org/W2064910514","https://openalex.org/W2084812512","https://openalex.org/W2088622335","https://openalex.org/W2092910747","https://openalex.org/W2107976320","https://openalex.org/W2110417041","https://openalex.org/W2135160607","https://openalex.org/W2148603752","https://openalex.org/W2150709895","https://openalex.org/W2401415512","https://openalex.org/W2489822048","https://openalex.org/W2526516990","https://openalex.org/W2544053333","https://openalex.org/W2911989211","https://openalex.org/W2963604113","https://openalex.org/W2963769561","https://openalex.org/W3103100819","https://openalex.org/W4230367971","https://openalex.org/W4256144259"],"related_works":["https://openalex.org/W2384527366","https://openalex.org/W2285494230","https://openalex.org/W1989621828","https://openalex.org/W4236479416","https://openalex.org/W4244597144","https://openalex.org/W3122914545","https://openalex.org/W3148196241","https://openalex.org/W1606169643","https://openalex.org/W2032696560","https://openalex.org/W2411778156"],"abstract_inverted_index":{"This":[0],"work":[1],"proposes":[2],"a":[3,31],"robust":[4],"regression":[5,12,138],"framework":[6],"with":[7,94,110],"nonconvex":[8],"loss":[9,21],"function.":[10],"Two":[11],"formulations":[13],"are":[14,60,80],"presented":[15],"based":[16],"on":[17,122],"the":[18,27,35,40,55,77,85,104,111,129,136],"Laplace":[19],"kernel-induced":[20],"(LK-loss).":[22],"Moreover,":[23],"we":[24,145],"illustrate":[25],"that":[26,103,128],"LK-loss":[28,41],"function":[29],"is":[30,51],"nice":[32],"approximation":[33],"for":[34],"zero-norm.":[36],"However,":[37],"nonconvexity":[38],"of":[39,65,87,142],"makes":[42],"it":[43],"difficult":[44],"to":[45,53,83],"optimize.":[46],"A":[47],"continuous":[48],"optimization":[49],"method":[50],"developed":[52],"solve":[54],"proposed":[56,78,105,130],"framework.":[57],"The":[58,69],"problems":[59],"formulated":[61],"as":[62],"DC":[63,71],"(difference":[64],"convex":[66],"functions)":[67],"programming.":[68],"corresponding":[70],"algorithms":[72,79],"(DCAs)":[73],"converge":[74],"linearly.":[75],"Furthermore,":[76],"applied":[81],"directly":[82],"determine":[84],"hardness":[86],"licorice":[88],"seeds":[89],"using":[90],"near-infrared":[91],"spectral":[92,100],"data":[93,125,143],"noisy":[95],"input.":[96],"Experiments":[97,121],"in":[98,118,140],"eight":[99],"regions":[101],"show":[102],"methods":[106,131,139],"improve":[107],"generalization":[108],"compared":[109],"traditional":[112,137],"support":[113],"vector":[114],"regressions":[115],"(SVR),":[116],"especially":[117],"high-frequency":[119],"regions.":[120],"several":[123],"benchmark":[124],"sets":[126,144],"demonstrate":[127],"achieve":[132],"better":[133],"results":[134],"than":[135],"most":[141],"have":[146],"considered.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}