{"id":"https://openalex.org/W2625003768","doi":null,"title":"Randomized Machine Learning Approaches: Recent Developments and Challenges","display_name":"Randomized Machine Learning Approaches: Recent Developments and Challenges","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2625003768","mag":"2625003768"},"language":"en","primary_location":{"id":"pmh:oai:arpi.unipi.it:11568/851913","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/11568/851913","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5011604061","display_name":"Claudio Gallicchio","orcid":"https://orcid.org/0000-0002-6692-2564","observed_orcids":["https://orcid.org/0000-0002-6692-2564"]},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudio Gallicchio","raw_affiliation_strings":["University of Pisa, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6692-2564","affiliations":[{"raw_affiliation_string":"University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081768850","display_name":"Jos\u00e9 D. Mart\u00edn\u2010Guerrero","orcid":"https://orcid.org/0000-0001-9378-0285","observed_orcids":["https://orcid.org/0000-0001-9378-0285"]},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jos\u00e9 D. Mart\u00edn\u2010Guerrero","raw_affiliation_strings":["Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":"https://orcid.org/0000-0001-9378-0285","affiliations":[{"raw_affiliation_string":"Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010923663","display_name":"Alessio Micheli","orcid":"https://orcid.org/0000-0001-5764-5238","observed_orcids":["https://orcid.org/0000-0001-5764-5238"]},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessio Micheli","raw_affiliation_strings":["University of Pisa, Pisa, Italy"],"raw_orcid":"https://orcid.org/0000-0001-5764-5238","affiliations":[{"raw_affiliation_string":"University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063325355","display_name":"Emilio Soria\u2010Olivas","orcid":"https://orcid.org/0000-0002-9148-8405","observed_orcids":["https://orcid.org/0000-0002-9148-8405"]},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Emilio Soria\u2010Olivas","raw_affiliation_strings":["Universitat de Val\u00e8ncia, Valencia, Spain"],"raw_orcid":"https://orcid.org/0000-0002-9148-8405","affiliations":[{"raw_affiliation_string":"Universitat de Val\u00e8ncia, Valencia, Spain","institution_ids":["https://openalex.org/I16097986"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6429,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9343691,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"77","last_page":"86"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8687000274658203,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10320","display_name":"Neural Networks and Applications","score":0.8687000274658203,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.07169999927282333,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.014700000174343586,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/random-forest","display_name":"random forest","score":0.8090000152587891},{"id":"https://openalex.org/keywords/random-neural-networks","display_name":"random neural networks","score":0.7910000085830688},{"id":"https://openalex.org/keywords/random-weights","display_name":"random weights","score":0.7350000143051147},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.9409999847412109},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.9980000257492065},{"id":"https://openalex.org/keywords/dynamical-systems","display_name":"dynamical systems","score":0.7519999742507935},{"id":"https://openalex.org/keywords/structured-domains","display_name":"structured domains","score":0.625}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6771607398986816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4847252368927002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4619458317756653}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arpi.unipi.it:11568/851913","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/11568/851913","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:2625003768","doi":null,"is_oa":false,"landing_page_url":"http://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2017-4.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421047","display_name":"The European Symposium on Artificial Neural Networks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"The European Symposium on Artificial Neural Networks","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W479801","https://openalex.org/W94523489","https://openalex.org/W1494248188","https://openalex.org/W1503398984","https://openalex.org/W1520795727","https://openalex.org/W1569512666","https://openalex.org/W1590183771","https://openalex.org/W1601254443","https://openalex.org/W1926592634","https://openalex.org/W2000904666","https://openalex.org/W2011975175","https://openalex.org/W2012638612","https://openalex.org/W2040870580","https://openalex.org/W2050518168","https://openalex.org/W2056132907","https://openalex.org/W2070922095","https://openalex.org/W2097998348","https://openalex.org/W2103179919","https://openalex.org/W2111072639","https://openalex.org/W2118706537","https://openalex.org/W2121971770","https://openalex.org/W2125091774","https://openalex.org/W2144572495","https://openalex.org/W2147880316","https://openalex.org/W2148143831","https://openalex.org/W2150039113","https://openalex.org/W2153513200","https://openalex.org/W2161278885","https://openalex.org/W2171865010","https://openalex.org/W2286961399","https://openalex.org/W2294916050","https://openalex.org/W2342814244","https://openalex.org/W2404607452","https://openalex.org/W2493920898","https://openalex.org/W2505582771","https://openalex.org/W2515529155","https://openalex.org/W2556430174","https://openalex.org/W2586160710","https://openalex.org/W2587524409","https://openalex.org/W2607255151","https://openalex.org/W2608997467","https://openalex.org/W2734733294","https://openalex.org/W2754311932","https://openalex.org/W2902237733","https://openalex.org/W2902418097","https://openalex.org/W2902600288","https://openalex.org/W2903309440","https://openalex.org/W2963473470"],"related_works":["https://openalex.org/W2902352290","https://openalex.org/W3008311476","https://openalex.org/W2586160710","https://openalex.org/W4252657966","https://openalex.org/W7204125096","https://openalex.org/W4285026790","https://openalex.org/W2560247988","https://openalex.org/W2286961399","https://openalex.org/W6906700043","https://openalex.org/W3201406253"],"abstract_inverted_index":{"Randomness":[0],"has":[1],"always":[2],"been":[3,81],"present":[4],"in":[5,10,25,39,103,107,121],"one":[6],"or":[7],"other":[8],"form":[9],"Machine":[11],"Learning":[12],"(ML)":[13],"models.":[14],"The":[15],"last":[16],"few":[17],"years":[18],"have":[19,80],"seen":[20],"a":[21,34,44,74],"change":[22],"of":[23,28,43,77,110],"role":[24],"the":[26,47,57,62,89,93,104,108],"use":[27,94],"randomness,":[29],"which":[30,79],"is":[31],"no":[32],"longer":[33],"specific":[35],"and":[36,117],"accessory":[37],"improvement":[38],"very":[40],"particular":[41],"aspects":[42],"model,":[45],"but":[46],"main":[48],"theoretical":[49],"basis":[50],"that":[51],"supports":[52],"some":[53],"ML":[54],"methods,":[55],"e.g.,":[56],"well-known":[58],"random":[59,97],"forests.":[60],"In":[61],"Neural":[63],"Network":[64],"(NN)":[65],"area,":[66],"since":[67],"its":[68],"origins,":[69],"randomness":[70],"gave":[71],"rise":[72],"to":[73],"rich":[75],"set":[76],"models,":[78],"recently":[82],"exploited":[83],"especially":[84,102],"for":[85,119],"efficiency":[86],"aims.":[87],"However,":[88],"bias":[90],"induced":[91],"by":[92],"NN":[95],"with":[96],"weights":[98],"deserves":[99],"further":[100],"analysis,":[101],"novel":[105],"advances":[106],"fields":[109],"deep":[111],"NNs,":[112],"dynamical":[113],"systems":[114],"(Recurrent":[115],"NN),":[116],"NNs":[118],"learning":[120],"structured":[122],"domains.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2017-06-23T00:00:00"}